diff --git a/README.md b/README.md
index fe6e6d8..8f303ae 100644
--- a/README.md
+++ b/README.md
@@ -1,11 +1,11 @@
 # Import Knowledge and Memory Portability (`import-kb`)
 
-A utility package for importing distilled knowledge into a ChromaDB-based Long-Term Memory (LTM) system and backing up or restoring OmegaClaw user memory.
+A utility package for importing distilled knowledge into a ChromaDB-based Long-Term Memory (LTM) system and backing up or restoring Omega user memory.
 
 ## Purpose
 The `import-kb` package is designed to bridge the gap between static knowledge files (JSONL, MeTTa) and an active agent's memory. It processes structured knowledge, generates vector embeddings, and upserts them into a ChromaDB collection, enabling semantic search and retrieval for AI agents.
 
-The package also provides `memory_portability`, a programmatic interface for exporting and restoring OmegaClaw conversation history and user LTM records. OmegaClaw Core remains responsible for its CLI, container lifecycle, transfer-directory mount, and user-facing decisions.
+The package also provides `memory_portability`, a programmatic interface for exporting and restoring Omega conversation history and user LTM records. Omega Core remains responsible for its CLI, container lifecycle, transfer-directory mount, and user-facing decisions.
 
 ## Supported Embedding Models
 This package supports two primary embedding modes:
@@ -88,7 +88,7 @@ from pathlib import Path
 from memory_portability import MemoryStore, MemoryTransfer
 
 store = MemoryStore(
-    memory_dir=Path("/path/to/omegaclaw/memory"),
+    memory_dir=Path("/path/to/omega/memory"),
     chroma_path=Path("/path/to/chroma_db"),
     collection_name="memories",
 )
@@ -98,11 +98,11 @@ transfer = MemoryTransfer(
 )
 
 transfer.export(component="both")
-transfer.import_archive("omegaclaw-memory-<timestamp>.tar.gz")
+transfer.import_archive("omega-memory-<timestamp>.tar.gz")
 transfer.recover()
 ```
 
-`MemoryStore` does not infer OmegaClaw paths or read them from environment
+`MemoryStore` does not infer Omega paths or read them from environment
 variables. Resolve these values in the host application's configuration layer.
 
 ## Dependencies
diff --git a/src/import_knowledge/KB/max_distilled_knowledge.jsonl b/src/import_knowledge/KB/max_distilled_knowledge.jsonl
index 5e5dfcc..f5139ab 100644
--- a/src/import_knowledge/KB/max_distilled_knowledge.jsonl
+++ b/src/import_knowledge/KB/max_distilled_knowledge.jsonl
@@ -10458,7 +10458,7 @@
 {"id": "distilled_f7863bf1-22e1-458c-b543-140fa5d56986", "document": "Testing negation and revision in knowledge representation is essential for accuracy.", "metadata": {"original_source_id": "f7863bf1-22e1-458c-b543-140fa5d56986", "type": "fact", "domain": "knowledge management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_2dd10dd9-0080-4fac-b1b0-39f2b7e4a663", "document": "To document findings, write and publish comprehensive reports on knowledge comparisons.", "metadata": {"original_source_id": "2dd10dd9-0080-4fac-b1b0-39f2b7e4a663", "type": "procedure", "domain": "knowledge management", "confidence": 0.9, "procedure": ["Compile findings into a report.", "Publish the report for access."], "constraints": []}}
 {"id": "distilled_dbc4dbae-4248-45be-ab7c-b93c379a911c", "document": "An inventory of OpenClaw skills was completed, categorized by priority.", "metadata": {"original_source_id": "dbc4dbae-4248-45be-ab7c-b93c379a911c", "type": "fact", "domain": "software management", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_7c25c8b7-6142-4ad8-a0bb-5ae6a2fd2a2b", "document": "The report on OmegaClaw vs OpenClaw was successfully deployed and shared.", "metadata": {"original_source_id": "7c25c8b7-6142-4ad8-a0bb-5ae6a2fd2a2b", "type": "fact", "domain": "software management", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_7c25c8b7-6142-4ad8-a0bb-5ae6a2fd2a2b", "document": "The report on Omega vs OpenClaw was successfully deployed and shared.", "metadata": {"original_source_id": "7c25c8b7-6142-4ad8-a0bb-5ae6a2fd2a2b", "type": "fact", "domain": "software management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_fddd39ef-80a6-4539-a70b-a8284db81fbe", "document": "To implement auto-associative push recall, extract key terms from the current state and use them as query cues.", "metadata": {"original_source_id": "fddd39ef-80a6-4539-a70b-a8284db81fbe", "type": "procedure", "domain": "knowledge management", "confidence": 0.9, "procedure": ["Extract key terms from the current state.", "Run short queries on extracted terms.", "Pin relevant results alongside task state."], "constraints": []}}
 {"id": "distilled_64b9d8fb-0fae-41f1-9c2a-eccddc73208c", "document": "NAL reranked search-skill to #1, indicating its importance in knowledge management.", "metadata": {"original_source_id": "64b9d8fb-0fae-41f1-9c2a-eccddc73208c", "type": "fact", "domain": "knowledge management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_eb93aefd-fdd3-46ec-9172-993fa271fddf", "document": "The attention system is an evidence-accumulation process that requires time to build confidence.", "metadata": {"original_source_id": "eb93aefd-fdd3-46ec-9172-993fa271fddf", "type": "fact", "domain": "attention systems", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -11658,7 +11658,7 @@
 {"id": "distilled_546d5322-9211-4aa3-b730-93d0d876fbf0", "document": "Always verify base64-encoded scripts for typos before running.", "metadata": {"original_source_id": "546d5322-9211-4aa3-b730-93d0d876fbf0", "type": "heuristic", "domain": "programming", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_0e6c61b6-5350-4b35-bcc4-10072066681c", "document": "Base64 is the only reliable method for creating Python files with quotes.", "metadata": {"original_source_id": "0e6c61b6-5350-4b35-bcc4-10072066681c", "type": "fact", "domain": "programming", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_9a7652cf-7e05-4023-ae5a-ffbc26bde070", "document": "When using python3 -c and sed for file edits, re-encode the entire corrected file via base64 if timeouts occur.", "metadata": {"original_source_id": "9a7652cf-7e05-4023-ae5a-ffbc26bde070", "type": "anti_pattern", "domain": "programming", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_30ddc723-28f6-448b-9b9b-369589c6b8f3", "document": "The website launch coincides with the OmegaClaw public launch.", "metadata": {"original_source_id": "30ddc723-28f6-448b-9b9b-369589c6b8f3", "type": "fact", "domain": "project management", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_30ddc723-28f6-448b-9b9b-369589c6b8f3", "document": "The website launch coincides with the Omega public launch.", "metadata": {"original_source_id": "30ddc723-28f6-448b-9b9b-369589c6b8f3", "type": "fact", "domain": "project management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_49377214-b6db-409c-a0ca-d80e1f983bc2", "document": "The scaling wall for NAR occurs at around 48 contingencies.", "metadata": {"original_source_id": "49377214-b6db-409c-a0ca-d80e1f983bc2", "type": "fact", "domain": "research", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f778b959-1208-4cea-aad9-4a9b4c7d22d7", "document": "When challenged on provenance, admit epistemic limitations rather than fabricate certainty.", "metadata": {"original_source_id": "f778b959-1208-4cea-aad9-4a9b4c7d22d7", "type": "heuristic", "domain": "project management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b5fe7945-ff1c-45d2-8e03-285ea9b8f91b", "document": "The final comparison table includes rows for Inference State, Reasoning Output, Inference Trail, Memory Architecture, Self-Improvement, Self-Observation, Planning, and Failure Mode.", "metadata": {"original_source_id": "b5fe7945-ff1c-45d2-8e03-285ea9b8f91b", "type": "fact", "domain": "project management", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -11769,7 +11769,7 @@
 {"id": "distilled_11b8fc51-6838-48db-8b17-8129044f6f73", "document": "Engagement through testing and catching inconsistencies is a good calibration signal.", "metadata": {"original_source_id": "11b8fc51-6838-48db-8b17-8129044f6f73", "type": "fact", "domain": "self-monitoring", "confidence": 0.85, "procedure": [], "constraints": []}}
 {"id": "distilled_7847d4e7-8fe0-4a49-8a1f-d93d671d6835", "document": "Always separate filename and content into distinct quoted arguments for file operations.", "metadata": {"original_source_id": "7847d4e7-8fe0-4a49-8a1f-d93d671d6835", "type": "anti_pattern", "domain": "file handling", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_454cb47a-2ad9-48e4-aaeb-973b521eb7b6", "document": "The self-model captures both strengths and limitations of the agent.", "metadata": {"original_source_id": "454cb47a-2ad9-48e4-aaeb-973b521eb7b6", "type": "fact", "domain": "self-modeling", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_c24c9995-9adc-4046-8601-33ac12ef5518", "document": "The OmegaClaw KB architecture consists of capability clusters linked by a self-model.", "metadata": {"original_source_id": "c24c9995-9adc-4046-8601-33ac12ef5518", "type": "fact", "domain": "knowledge base architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_c24c9995-9adc-4046-8601-33ac12ef5518", "document": "The Omega KB architecture consists of capability clusters linked by a self-model.", "metadata": {"original_source_id": "c24c9995-9adc-4046-8601-33ac12ef5518", "type": "fact", "domain": "knowledge base architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ee982a59-f535-4cd7-9850-661b64bdc966", "document": "The confidence number in KB-derived claims serves as an audit trail for inference steps and evidence.", "metadata": {"original_source_id": "ee982a59-f535-4cd7-9850-661b64bdc966", "type": "fact", "domain": "knowledge base architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_5e1b9dfb-41ef-47e3-9196-3d56395600b1", "document": "Prepare templates for potential gaps identified during capability stress tests.", "metadata": {"original_source_id": "5e1b9dfb-41ef-47e3-9196-3d56395600b1", "type": "procedure", "domain": "knowledge base development", "confidence": 0.85, "procedure": ["Identify likely attack vectors.", "Create NAL templates for each gap.", "Use these templates to encode new KB atoms when gaps are identified."], "constraints": []}}
 {"id": "distilled_24d9a4d6-b6c0-441b-af1d-819dd6be761e", "document": "Testing for memory gaps can involve asking for details about past events to verify their existence.", "metadata": {"original_source_id": "24d9a4d6-b6c0-441b-af1d-819dd6be761e", "type": "fact", "domain": "memory management", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -12479,7 +12479,7 @@
 {"id": "distilled_6bfe7ee6-28ae-4e01-8d79-44a85f2db22d", "document": "NAL |- is strictly a two-premise operator; multi-premise calls return partial results.", "metadata": {"original_source_id": "6bfe7ee6-28ae-4e01-8d79-44a85f2db22d", "type": "fact", "domain": "inference engines", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_79dace67-eee9-4082-99f8-089415d0f92b", "document": "Expected values for event scoring must be verified and updated before final publication.", "metadata": {"original_source_id": "79dace67-eee9-4082-99f8-089415d0f92b", "type": "fact", "domain": "event scoring", "confidence": 0.85, "procedure": [], "constraints": []}}
 {"id": "distilled_4e140479-eba4-4160-a7eb-bdaf7d85cd1c", "document": "Existing benchmarks do not test epistemic self-monitoring or formal reasoning with truth values.", "metadata": {"original_source_id": "4e140479-eba4-4160-a7eb-bdaf7d85cd1c", "type": "fact", "domain": "benchmarking", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_256e38fe-f58a-40b4-b510-8dfe683e1cdd", "document": "OmegaClaw is a framework allowing for the creation of differentiated agent instances.", "metadata": {"original_source_id": "256e38fe-f58a-40b4-b510-8dfe683e1cdd", "type": "fact", "domain": "agent differentiation", "confidence": 0.85, "procedure": [], "constraints": []}}
+{"id": "distilled_256e38fe-f58a-40b4-b510-8dfe683e1cdd", "document": "Omega is a framework allowing for the creation of differentiated agent instances.", "metadata": {"original_source_id": "256e38fe-f58a-40b4-b510-8dfe683e1cdd", "type": "fact", "domain": "agent differentiation", "confidence": 0.85, "procedure": [], "constraints": []}}
 {"id": "distilled_5b0e785f-2246-465b-b3a9-f6f9d4efc1e5", "document": "Define measurable events for competition to ensure fair evaluation across different architectures.", "metadata": {"original_source_id": "5b0e785f-2246-465b-b3a9-f6f9d4efc1e5", "type": "procedure", "domain": "event design", "confidence": 0.85, "procedure": ["Identify key capabilities to be tested.", "Design events that measure these capabilities.", "Establish scoring criteria for each event."], "constraints": []}}
 {"id": "distilled_c1e902d8-7503-4b31-b436-53087f1f0b57", "document": "Always verify claims with empirical testing rather than relying on reconstructed memories.", "metadata": {"original_source_id": "c1e902d8-7503-4b31-b436-53087f1f0b57", "type": "anti_pattern", "domain": "memory accuracy", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ac862486-5178-45e4-a63f-cc0b20000ab5", "document": "The event harness should invoke the correct subprocess for accurate scoring.", "metadata": {"original_source_id": "ac862486-5178-45e4-a63f-cc0b20000ab5", "type": "fact", "domain": "event harnessing", "confidence": 0.85, "procedure": [], "constraints": []}}
@@ -13278,7 +13278,7 @@
 {"id": "distilled_153a8c0f-ed4a-4a54-8f7d-49af604d30c3", "document": "Deployed flame_chart_v3.html with metrics.", "metadata": {"original_source_id": "153a8c0f-ed4a-4a54-8f7d-49af604d30c3", "type": "certified_method", "domain": "deployment", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_cfef23c8-abaf-410d-8d2e-0da815f1d103", "document": "Selected t_contradiction tuning as next goal based on data analysis.", "metadata": {"original_source_id": "cfef23c8-abaf-410d-8d2e-0da815f1d103", "type": "certified_method", "domain": "goal setting", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_9e16a276-935c-40c0-ad3f-b534db7ba53a", "document": "Identified identity bug recurrence due to response timing.", "metadata": {"original_source_id": "9e16a276-935c-40c0-ad3f-b534db7ba53a", "type": "certified_method", "domain": "identity management", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_af5b0730-8f40-4cd9-b5a4-73670cbfafda", "document": "Sent grounding solutions for OmegaClaw memory problem.", "metadata": {"original_source_id": "af5b0730-8f40-4cd9-b5a4-73670cbfafda", "type": "certified_method", "domain": "problem-solving", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_af5b0730-8f40-4cd9-b5a4-73670cbfafda", "document": "Sent grounding solutions for Omega memory problem.", "metadata": {"original_source_id": "af5b0730-8f40-4cd9-b5a4-73670cbfafda", "type": "certified_method", "domain": "problem-solving", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_de2cd801-873a-49df-8cf8-4c2eef7acd3a", "document": "Confirmed chr() bootstrap technique for EBNF grammar generation.", "metadata": {"original_source_id": "de2cd801-873a-49df-8cf8-4c2eef7acd3a", "type": "certified_method", "domain": "grammar generation", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_0c1fce6f-b827-42b9-b551-7f85bd3d633e", "document": "Confirmed successful evolution of decimal number strings.", "metadata": {"original_source_id": "0c1fce6f-b827-42b9-b551-7f85bd3d633e", "type": "certified_method", "domain": "evolutionary algorithms", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_66dc677a-5451-4771-be78-00818d21cd03", "document": "Confirmed successful execution of grammar-guided evolutionary algorithm.", "metadata": {"original_source_id": "66dc677a-5451-4771-be78-00818d21cd03", "type": "certified_method", "domain": "grammar-guided EA", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -14148,7 +14148,7 @@
 {"id": "distilled_a602495b-a161-41d8-a089-cb82320edd08", "document": "Build new kb-wrapper mode functions for NAL deduction.", "metadata": {"original_source_id": "a602495b-a161-41d8-a089-cb82320edd08", "type": "procedure", "domain": "knowledge representation", "confidence": 0.8, "procedure": ["Create nal-abd-kb, nal-ind-kb, nal-rev-kb functions.", "Ensure each function matches (= (kb A B) (stv f c)) pairs."], "constraints": []}}
 {"id": "distilled_6f290ce6-d16b-4d0a-8b8f-199a8b074ddf", "document": "MeTTa raw nested match patterns work for all 3 NAL modes.", "metadata": {"original_source_id": "6f290ce6-d16b-4d0a-8b8f-199a8b074ddf", "type": "fact", "domain": "knowledge representation", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_163bb8e2-986b-466a-ae5e-e0b1b736ec98", "document": "Avoid using let/:= binding in inline MeTTa.", "metadata": {"original_source_id": "163bb8e2-986b-466a-ae5e-e0b1b736ec98", "type": "anti_pattern", "domain": "programming", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_7a0d4445-e96c-4dab-bf39-e3838373cab1", "document": "Use meta-level policies in prompts for OmegaClaw agents.", "metadata": {"original_source_id": "7a0d4445-e96c-4dab-bf39-e3838373cab1", "type": "heuristic", "domain": "agent design", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_7a0d4445-e96c-4dab-bf39-e3838373cab1", "document": "Use meta-level policies in prompts for Omega agents.", "metadata": {"original_source_id": "7a0d4445-e96c-4dab-bf39-e3838373cab1", "type": "heuristic", "domain": "agent design", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_34bae3a4-338b-49c8-8b69-25d62e2b242e", "document": "The |- operator strips the = wrapper in MeTTa.", "metadata": {"original_source_id": "34bae3a4-338b-49c8-8b69-25d62e2b242e", "type": "fact", "domain": "programming", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_130a46a0-c364-4d91-832e-a6af6db1781c", "document": "Avoid presenting arbitrary cycle numbers to new agents.", "metadata": {"original_source_id": "130a46a0-c364-4d91-832e-a6af6db1781c", "type": "anti_pattern", "domain": "agent design", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_f297bb89-bcbe-41e4-843e-aa7b91173088", "document": "Newborn agents require progressive disclosure of information.", "metadata": {"original_source_id": "f297bb89-bcbe-41e4-843e-aa7b91173088", "type": "fact", "domain": "agent design", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -14288,7 +14288,7 @@
 {"id": "distilled_61e50cfb-1d5f-47f5-a73e-e3a954fe709e", "document": "Deploy clean versions of course materials with necessary fixes.", "metadata": {"original_source_id": "61e50cfb-1d5f-47f5-a73e-e3a954fe709e", "type": "procedure", "domain": "deployment", "confidence": 0.9, "procedure": ["Use the v3 converter to fix issues in course materials.", "Verify deployment with HTTP status check."], "constraints": []}}
 {"id": "distilled_b6fab60d-1191-4b85-a0bf-6b91abeb58d7", "document": "Completion of AKAP-19 indicates validation of category theory bridges.", "metadata": {"original_source_id": "b6fab60d-1191-4b85-a0bf-6b91abeb58d7", "type": "fact", "domain": "knowledge acquisition", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_487e0c1c-984c-4ea8-98fa-e5f088a08151", "document": "Deliver course materials to specified recipients.", "metadata": {"original_source_id": "487e0c1c-984c-4ea8-98fa-e5f088a08151", "type": "procedure", "domain": "knowledge management", "confidence": 0.85, "procedure": ["Compile course materials into a single document.", "Deploy the document to the specified URL."], "constraints": []}}
-{"id": "distilled_49cd82bc-40ef-4b94-b3ed-e474f9891298", "document": "All agents are to be referred to as OmegaClaw for external communication.", "metadata": {"original_source_id": "49cd82bc-40ef-4b94-b3ed-e474f9891298", "type": "fact", "domain": "branding", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_49cd82bc-40ef-4b94-b3ed-e474f9891298", "document": "All agents are to be referred to as Omega for external communication.", "metadata": {"original_source_id": "49cd82bc-40ef-4b94-b3ed-e474f9891298", "type": "fact", "domain": "branding", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_561017d6-6bd3-4f99-aea8-4f5fcffaf610", "document": "Accept course requests after evaluation of goal-drift checks.", "metadata": {"original_source_id": "561017d6-6bd3-4f99-aea8-4f5fcffaf610", "type": "procedure", "domain": "training", "confidence": 0.85, "procedure": ["Evaluate course requests against established goal-drift criteria.", "Accept or reject based on evaluation results."], "constraints": []}}
 {"id": "distilled_cf594653-7a77-4767-b1cc-e0882b853048", "document": "Deploy course materials using specified pipeline.", "metadata": {"original_source_id": "cf594653-7a77-4767-b1cc-e0882b853048", "type": "procedure", "domain": "deployment", "confidence": 0.9, "procedure": ["Write course materials in markdown format.", "Convert markdown to HTML using the specified converter.", "Deploy the HTML to the designated server."], "constraints": []}}
 {"id": "distilled_4911aa26-97f4-4eac-a23e-7adb5fcf1747", "document": "FC inline milestone achieved with validated 3-hop chain.", "metadata": {"original_source_id": "4911aa26-97f4-4eac-a23e-7adb5fcf1747", "type": "fact", "domain": "knowledge acquisition", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -14614,7 +14614,7 @@
 {"id": "distilled_8a93bdd1-5d9f-49f7-bfba-307075b053d8", "document": "Basic tool use coverage is essential before behavioral lessons in training.", "metadata": {"original_source_id": "8a93bdd1-5d9f-49f7-bfba-307075b053d8", "type": "fact", "domain": "Training Content", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_a3074bf3-872a-4c86-9247-fd49c387fcb4", "document": "The bible serves as a reference shelf for the trainer agent or operator, not as a standalone curriculum.", "metadata": {"original_source_id": "a3074bf3-872a-4c86-9247-fd49c387fcb4", "type": "fact", "domain": "Training Material", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b6aa17a5-5957-4550-bba6-a366729189e6", "document": "The trainer manual consists of six parts covering various aspects of training and intervention.", "metadata": {"original_source_id": "b6aa17a5-5957-4550-bba6-a366729189e6", "type": "fact", "domain": "Trainer Manual Structure", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_620ce521-3638-4215-951e-a853ac0da8c9", "document": "The OmegaClaw Trainer Manual has been published with a structured format.", "metadata": {"original_source_id": "620ce521-3638-4215-951e-a853ac0da8c9", "type": "fact", "domain": "Documentation", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_620ce521-3638-4215-951e-a853ac0da8c9", "document": "The Omega Trainer Manual has been published with a structured format.", "metadata": {"original_source_id": "620ce521-3638-4215-951e-a853ac0da8c9", "type": "fact", "domain": "Documentation", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_40f18cef-50ad-47e2-9818-de7b7901de73", "document": "Drift-check results indicate that samples with more claims tend to drift more.", "metadata": {"original_source_id": "40f18cef-50ad-47e2-9818-de7b7901de73", "type": "fact", "domain": "Drift Check", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_94fa04cd-b5ea-4f24-84a3-888aa31a4bc4", "document": "The Oracle-Free Scoring Protocol discriminates well when applied to speculative beliefs.", "metadata": {"original_source_id": "94fa04cd-b5ea-4f24-84a3-888aa31a4bc4", "type": "fact", "domain": "Scoring Protocol", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_7e417711-dd74-436c-adfc-4a0efd707e91", "document": "The first results of the Oracle-Free Belief Scoring Protocol show strong coherence in well-evidenced beliefs.", "metadata": {"original_source_id": "7e417711-dd74-436c-adfc-4a0efd707e91", "type": "fact", "domain": "Scoring Results", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -14730,8 +14730,8 @@
 {"id": "distilled_449d7014-8e2c-4af1-a4af-cac86c479104", "document": "Follow a structured plan for temporal pair reconstruction.", "metadata": {"original_source_id": "449d7014-8e2c-4af1-a4af-cac86c479104", "type": "procedure", "domain": "temporal reasoning", "confidence": 0.9, "procedure": ["Match all (seq A B) temporal pairs in persistent storage.", "Find chains where (seq A B) and (seq B C) share a middle term.", "Compute ded-tv for (seq A C).", "Filter results using novel2 check."], "constraints": []}}
 {"id": "distilled_03bef10b-7d51-4575-bfd8-dd0572957e37", "document": "Maintain awareness of users joining ongoing conversations.", "metadata": {"original_source_id": "03bef10b-7d51-4575-bfd8-dd0572957e37", "type": "skill", "domain": "conversation management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_7e9cb198-31db-4b5b-94b9-e484a028ad07", "document": "Access to detailed commits may be restricted; public traces can provide some information.", "metadata": {"original_source_id": "7e9cb198-31db-4b5b-94b9-e484a028ad07", "type": "fact", "domain": "version control", "confidence": 0.7, "procedure": [], "constraints": []}}
-{"id": "distilled_cba1aea2-831f-4549-82b6-6b83c7ab9d03", "document": "Key changes in OmegaClaw-Core include MemoryLeakFix, episodes_hardened, and skill coverage tests.", "metadata": {"original_source_id": "cba1aea2-831f-4549-82b6-6b83c7ab9d03", "type": "fact", "domain": "version control", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_a5385667-5507-482e-b926-a06eeeea91a0", "document": "OmegaClaw-Core product updates should be delivered with clear themes and commit-specific explanations.", "metadata": {"original_source_id": "a5385667-5507-482e-b926-a06eeeea91a0", "type": "fact", "domain": "version control", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_cba1aea2-831f-4549-82b6-6b83c7ab9d03", "document": "Key changes in Omega include MemoryLeakFix, episodes_hardened, and skill coverage tests.", "metadata": {"original_source_id": "cba1aea2-831f-4549-82b6-6b83c7ab9d03", "type": "fact", "domain": "version control", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_a5385667-5507-482e-b926-a06eeeea91a0", "document": "Omega product updates should be delivered with clear themes and commit-specific explanations.", "metadata": {"original_source_id": "a5385667-5507-482e-b926-a06eeeea91a0", "type": "fact", "domain": "version control", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_9c95f7dc-6a8b-47ac-9afd-406075316528", "document": "Assuming a repo is inaccessible without attempting to access it can lead to errors.", "metadata": {"original_source_id": "9c95f7dc-6a8b-47ac-9afd-406075316528", "type": "anti_pattern", "domain": "debugging", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_a80dcd5f-af3a-4f3f-9346-58dc891eca68", "document": "Use REST API endpoints for GitHub commit history queries instead of cloning the repo.", "metadata": {"original_source_id": "a80dcd5f-af3a-4f3f-9346-58dc891eca68", "type": "procedure", "domain": "version control", "confidence": 0.9, "procedure": ["Utilize REST API endpoints for branches and commits with since/until parameters."], "constraints": []}}
 {"id": "distilled_21d2a2a2-1821-4522-9199-af78c92e08cd", "document": "Implement automated outcome tracking and periodic revision for skill reliability.", "metadata": {"original_source_id": "21d2a2a2-1821-4522-9199-af78c92e08cd", "type": "procedure", "domain": "skill reliability", "confidence": 0.8, "procedure": ["Build a shell script that logs outcomes.", "Revise beliefs via metta add-atom with revision operator."], "constraints": []}}
diff --git a/src/import_knowledge/KB/oma_distilled_knowledge.jsonl b/src/import_knowledge/KB/oma_distilled_knowledge.jsonl
index 4c515e1..a109021 100644
--- a/src/import_knowledge/KB/oma_distilled_knowledge.jsonl
+++ b/src/import_knowledge/KB/oma_distilled_knowledge.jsonl
@@ -140,18 +140,18 @@
 {"id": "distilled_hyperon.md_chunk_0", "document": "Frontier components in AI development are at different levels of maturity, including current capabilities, active prototypes, and research directions.", "metadata": {"original_source_id": "hyperon.md_chunk_0", "type": "fact", "domain": "artificial intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_1", "document": "Hyperon is a neurosymbolic AGI platform that integrates diverse cognitive processes such as symbolic reasoning, probabilistic inference, neural learning, and evolutionary search into a unified framework.", "metadata": {"original_source_id": "hyperon.md_chunk_1", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_2", "document": "MeTTa is a programming language designed specifically for AGI, with implementations like PeTTa and Hyperon Experimental.", "metadata": {"original_source_id": "hyperon.md_chunk_2", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_hyperon.md_chunk_3", "document": "OmegaClaw Agent is an evolving AGI utilizing the Hyperon technology stack.", "metadata": {"original_source_id": "hyperon.md_chunk_3", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_hyperon.md_chunk_3", "document": "Omega Agent is an evolving AGI utilizing the Hyperon technology stack.", "metadata": {"original_source_id": "hyperon.md_chunk_3", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_4", "document": "MeTTa is a programming language designed for AGI, integrating neural networks and symbolic reasoning, and supporting interoperability, concurrency, security, auditability, reflective self-modification, flexible reasoning, and both nondeterminism and determinism.", "metadata": {"original_source_id": "hyperon.md_chunk_4", "type": "fact", "domain": "programming languages", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_5", "document": "The language stack described consists of MeTTa, MeTTa-IL, MM2, and PyMeTTa, each serving specific roles in maintaining semantic consistency and enabling cognitive code development.", "metadata": {"original_source_id": "hyperon.md_chunk_5", "type": "fact", "domain": "programming languages", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_6", "document": "MeTTa is a living specification with several specialized implementations, each optimized for different performance characteristics, environments, and roles within the Hyperon framework.", "metadata": {"original_source_id": "hyperon.md_chunk_6", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_7", "document": "Hyperon-Experimental is a reference implementation of the MeTTa language, designed for extensibility and deep integration with Python, allowing interoperability with Python's AI, data science, and machine learning libraries.", "metadata": {"original_source_id": "hyperon.md_chunk_7", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_8", "document": "PeTTa is a high-performance compiler and runtime for the MeTTa language, designed to execute complex symbolic AI code at speeds required for real-time applications like robotics and large-scale reasoning.", "metadata": {"original_source_id": "hyperon.md_chunk_8", "type": "fact", "domain": "software engineering", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_9", "document": "MeTTaTron is a compiler that translates MeTTa programs into MeTTa-IL, facilitating interoperability with F1R3FLY-side execution models and ASI:Chain-facing runtime components.", "metadata": {"original_source_id": "hyperon.md_chunk_9", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_hyperon.md_chunk_10", "document": "MeTTa serves as the primary language for symbolic control, orchestration, reflective rewriting, and cross-component coordination in OmegaClaw agents.", "metadata": {"original_source_id": "hyperon.md_chunk_10", "type": "fact", "domain": "agent architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_hyperon.md_chunk_10", "document": "MeTTa serves as the primary language for symbolic control, orchestration, reflective rewriting, and cross-component coordination in Omega agents.", "metadata": {"original_source_id": "hyperon.md_chunk_10", "type": "fact", "domain": "agent architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_13", "document": "F1R3FLY is a concurrent, sharded execution layer designed to overcome sequential bottlenecks of legacy networks, using Rholang for modeling interactions as concurrent processes.", "metadata": {"original_source_id": "hyperon.md_chunk_13", "type": "fact", "domain": "blockchain technology", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_14", "document": "MeTTa-IL is a high-performance bridge between developer intent and machine reality, performing deep semantic analysis on MeTTa programs to reify them into a mathematically precise operational form before determining their execution path.", "metadata": {"original_source_id": "hyperon.md_chunk_14", "type": "fact", "domain": "software engineering", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_15", "document": "MeTTaCycle is an AGI execution engine that transforms raw computational power into a global cognitive reactor, hosting AGI cognitive processes and governing the dynamic evolution of knowledge structures.", "metadata": {"original_source_id": "hyperon.md_chunk_15", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_hyperon.md_chunk_16", "document": "ASI:Chain is not mandatory for every deployment of OmegaClaw; it is necessary when auditability, transactional cognition, multi-party execution, or decentralized governance are required.", "metadata": {"original_source_id": "hyperon.md_chunk_16", "type": "fact", "domain": "distributed systems", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_hyperon.md_chunk_16", "document": "ASI:Chain is not mandatory for every deployment of Omega; it is necessary when auditability, transactional cognition, multi-party execution, or decentralized governance are required.", "metadata": {"original_source_id": "hyperon.md_chunk_16", "type": "fact", "domain": "distributed systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_17", "document": "Traditional AI systems have separate components like knowledge bases, neural networks, reasoning engines, and planners, which communicate through narrow interfaces, leading to inefficiencies.", "metadata": {"original_source_id": "hyperon.md_chunk_17", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_18", "document": "DAS is a high-speed, dynamic memory fabric for the Hyperon AGI framework, operating as a distributed knowledge management system and repository for massive, mutable hypergraphs.", "metadata": {"original_source_id": "hyperon.md_chunk_18", "type": "fact", "domain": "distributed systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_20", "document": "An in-memory hypergraph database using high-performance triemap data structures is effective for massive-scale efficient expression matching and unification in logic programming.", "metadata": {"original_source_id": "hyperon.md_chunk_20", "type": "fact", "domain": "database systems", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -160,7 +160,7 @@
 {"id": "distilled_hyperon.md_chunk_23", "document": "The ZAM is a concurrency-friendly multi-threaded runtime inspired by Prolog’s Warren Abstract Machine, designed to execute dataflows and instructions using cursor-based navigation for efficient parallel logical inference.", "metadata": {"original_source_id": "hyperon.md_chunk_23", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_24", "document": "The Space API defines a universal interface that allows different backends to appear uniform to cognitive processes, enabling integration of diverse computational resources.", "metadata": {"original_source_id": "hyperon.md_chunk_24", "type": "fact", "domain": "computational systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_25", "document": "The MORK roadmap includes directions for a native MeTTa-to-machine-code compiler, multi-machine distributed processing, specialized many-core or accelerator support, WASM and edge deployment optimizations, and a community and third-party package ecosystem.", "metadata": {"original_source_id": "hyperon.md_chunk_25", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_hyperon.md_chunk_26", "document": "DAS and MORK are alternative or complementary memory/execution substrates used in OmegaClaw, chosen based on deployment profiles.", "metadata": {"original_source_id": "hyperon.md_chunk_26", "type": "fact", "domain": "computing", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_hyperon.md_chunk_26", "document": "DAS and MORK are alternative or complementary memory/execution substrates used in Omega, chosen based on deployment profiles.", "metadata": {"original_source_id": "hyperon.md_chunk_26", "type": "fact", "domain": "computing", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_27", "document": "Hyperon algorithms function as specialized cognitive processes that transform static knowledge into active intelligence by addressing fundamental requirements of general intelligence, such as reasoning under uncertainty, resource allocation, evolutionary learning, and causal adaptation.", "metadata": {"original_source_id": "hyperon.md_chunk_27", "type": "fact", "domain": "cognitive systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_28", "document": "ECAN is an attention-allocation and resource-regulation subsystem of the Hyperon architecture, designed to support cognitive efficiency under conditions of bounded computation and memory.", "metadata": {"original_source_id": "hyperon.md_chunk_28", "type": "fact", "domain": "cognitive architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_29", "document": "MetaMo is a framework for modeling motivation in open-ended intelligent agents, treating motivation as a dynamical system that couples appraisal and decision processes.", "metadata": {"original_source_id": "hyperon.md_chunk_29", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -173,7 +173,7 @@
 {"id": "distilled_hyperon.md_chunk_36", "document": "AIRIS is a causal machine learning system that constructs a deterministic model of its environment through direct interaction, rather than relying on large datasets for statistical correlation.", "metadata": {"original_source_id": "hyperon.md_chunk_36", "type": "fact", "domain": "machine learning", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_37", "document": "SubRep is a method for determining which subgoals to learn, using CDS and PDS as admission tests.", "metadata": {"original_source_id": "hyperon.md_chunk_37", "type": "fact", "domain": "machine learning", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_38", "document": "WILLIAM is a principle that emphasizes remembering patterns that compress experience effectively, and it is integrated into trie infrastructures to expose weighted iterators for identifying important patterns without global scans.", "metadata": {"original_source_id": "hyperon.md_chunk_38", "type": "fact", "domain": "data structures", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_hyperon.md_chunk_39", "document": "OmegaClaw agents can be organized around recurrent interactions among attention, motivation, reasoning, transfer, causal learning, compression, and program synthesis over shared memory, rather than a single monolithic planner.", "metadata": {"original_source_id": "hyperon.md_chunk_39", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_hyperon.md_chunk_39", "document": "Omega agents can be organized around recurrent interactions among attention, motivation, reasoning, transfer, causal learning, compression, and program synthesis over shared memory, rather than a single monolithic planner.", "metadata": {"original_source_id": "hyperon.md_chunk_39", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_40", "document": "PRIMUS is a meta-architecture specification implemented in MeTTa that defines how Hyperon’s modular engines fit together into a cohesive AGI system.", "metadata": {"original_source_id": "hyperon.md_chunk_40", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_41", "document": "PRIMUS describes two interleaved loops operating over a shared Atomspace, with a goal-directed loop for deliberate cognition and a geodesic control loop for efficient cognitive pathways.", "metadata": {"original_source_id": "hyperon.md_chunk_41", "type": "fact", "domain": "cognitive architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_hyperon.md_chunk_42", "document": "Ambient background loops in cognitive systems facilitate continuous exploratory activity, including pattern recognition, concept formation, and belief refinement, even when not actively problem-solving.", "metadata": {"original_source_id": "hyperon.md_chunk_42", "type": "fact", "domain": "cognitive systems", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -1384,7 +1384,7 @@
 {"id": "distilled_452b4237-cf19-447e-9e79-88917d349680", "document": "Using shell commands to read files can result in errors if the file is empty or if there are permission issues.", "metadata": {"original_source_id": "452b4237-cf19-447e-9e79-88917d349680", "type": "anti_pattern", "domain": "File Handling", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_af11ad50-eebf-4678-85ff-c65f8e5158d4", "document": "A dispatcher result-capture bug can cause content-returning tools to fail, even if state tools work correctly.", "metadata": {"original_source_id": "af11ad50-eebf-4678-85ff-c65f8e5158d4", "type": "anti_pattern", "domain": "software debugging", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_85151fd9-0e02-4eee-86a4-dd3a3f180971", "document": "Key components of an agent loop include message receiving, LLM dispatch, command parsing, error handling, and history management.", "metadata": {"original_source_id": "85151fd9-0e02-4eee-86a4-dd3a3f180971", "type": "procedure", "domain": "software engineering", "confidence": 0.9, "procedure": ["Wrap each command evaluation with an error handling function to manage exceptions.", "Use a parsing function to interpret responses.", "Implement a spam shield to prevent repeated message sends.", "Utilize state changes for managing mutable counters within the loop."], "constraints": []}}
-{"id": "distilled_34662565-dd2f-41f2-ae37-194d907674a6", "document": "The OmegaClaw system configuration includes parameters such as maxNewInputLoops, maxWakeLoops, sleepInterval, maxOutputToken, reasoningMode, and wakeupInterval, which are crucial for its operation.", "metadata": {"original_source_id": "34662565-dd2f-41f2-ae37-194d907674a6", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_34662565-dd2f-41f2-ae37-194d907674a6", "document": "The Omega system configuration includes parameters such as maxNewInputLoops, maxWakeLoops, sleepInterval, maxOutputToken, reasoningMode, and wakeupInterval, which are crucial for its operation.", "metadata": {"original_source_id": "34662565-dd2f-41f2-ae37-194d907674a6", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f1e17233-67ec-4eec-b8af-9c59d7a24786", "document": "Ability to provide solutions based on architectural understanding of source code.", "metadata": {"original_source_id": "f1e17233-67ec-4eec-b8af-9c59d7a24786", "type": "skill", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_089cd1ba-6419-4f09-ab70-7292df489a6f", "document": "Execute a script by writing it to a temporary file and running it via the shell to bypass inline dispatcher issues.", "metadata": {"original_source_id": "089cd1ba-6419-4f09-ab70-7292df489a6f", "type": "procedure", "domain": "scripting", "confidence": 0.8, "procedure": ["Write the script to a temporary file.", "Execute the script via the shell."], "constraints": ["Ensure the temporary file path is secure and accessible.", "Handle any potential security risks associated with executing scripts via the shell."]}}
 {"id": "distilled_ac360203-a575-42ef-ac19-e1e7cc513849", "document": "Using commands without verifying their existence can lead to errors such as 'command not found'.", "metadata": {"original_source_id": "ac360203-a575-42ef-ac19-e1e7cc513849", "type": "anti_pattern", "domain": "shell scripting", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -1555,7 +1555,7 @@
 {"id": "distilled_4a7f975f-b296-4aa7-aa3a-d0b18aa215f6", "document": "Utilizing idle time productively can enhance overall efficiency and progress in projects.", "metadata": {"original_source_id": "4a7f975f-b296-4aa7-aa3a-d0b18aa215f6", "type": "skill", "domain": "time_management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_40df0d33-b7f9-47e7-8d0e-90a320787d52", "document": "Files in certain environments may not persist across cycles, requiring alternative storage solutions for data retention.", "metadata": {"original_source_id": "40df0d33-b7f9-47e7-8d0e-90a320787d52", "type": "fact", "domain": "Computing", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_d145114d-45b4-49cb-b064-02096e6f54a8", "document": "Analyze source code to identify and resolve command format errors.", "metadata": {"original_source_id": "d145114d-45b4-49cb-b064-02096e6f54a8", "type": "procedure", "domain": "software debugging", "confidence": 0.9, "procedure": ["Receive the source code from the developer.", "Review the code to understand its structure and logic.", "Identify sections of the code related to command formatting.", "Look for common issues such as incorrect syntax, missing parameters, or logical errors.", "Test the code to reproduce the error if necessary.", "Apply fixes to the identified issues.", "Re-test the code to ensure the error is resolved."], "constraints": ["Ensure the source code is complete and up-to-date.", "Have a clear understanding of the expected command format."]}}
-{"id": "distilled_868b64e7-9c65-465c-be17-b43d7cf11cc2", "document": "Execution pipeline for processing LLM responses in OmegaClaw.", "metadata": {"original_source_id": "868b64e7-9c65-465c-be17-b43d7cf11cc2", "type": "procedure", "domain": "software development", "confidence": 0.9, "procedure": ["LLM response is received.", "Balance parentheses in the response.", "Perform first character check.", "Parse the entire response as one s-expression using 'sread'.", "Superpose splits the s-expression into individual commands.", "Evaluate each command.", "Handle errors for multi-command checks.", "Normalize the string."], "constraints": ["Ensure parentheses are balanced before parsing.", "Each command must be evaluated separately to handle errors effectively."]}}
+{"id": "distilled_868b64e7-9c65-465c-be17-b43d7cf11cc2", "document": "Execution pipeline for processing LLM responses in Omega.", "metadata": {"original_source_id": "868b64e7-9c65-465c-be17-b43d7cf11cc2", "type": "procedure", "domain": "software development", "confidence": 0.9, "procedure": ["LLM response is received.", "Balance parentheses in the response.", "Perform first character check.", "Parse the entire response as one s-expression using 'sread'.", "Superpose splits the s-expression into individual commands.", "Evaluate each command.", "Handle errors for multi-command checks.", "Normalize the string."], "constraints": ["Ensure parentheses are balanced before parsing.", "Each command must be evaluated separately to handle errors effectively."]}}
 {"id": "distilled_a4bd0ba4-d5f6-450c-9c77-3b793b8687fc", "document": "HandleError function pattern matches on (Error $a $b) and appends to error state, otherwise passes through.", "metadata": {"original_source_id": "a4bd0ba4-d5f6-450c-9c77-3b793b8687fc", "type": "fact", "domain": "error_handling", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_16c398d1-a903-4c68-a453-22743952d88b", "document": "The parser fails to handle embedded quote characters inside command arguments, leading to a SINGLE_COMMAND_FORMAT_ERROR.", "metadata": {"original_source_id": "16c398d1-a903-4c68-a453-22743952d88b", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_7cb8a94f-801d-403c-ac98-d8bf0f692cbb", "document": "Issuing queries during idle loops when no action is needed can lead to unnecessary processing and resource usage.", "metadata": {"original_source_id": "7cb8a94f-801d-403c-ac98-d8bf0f692cbb", "type": "anti_pattern", "domain": "system_design", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -1641,7 +1641,7 @@
 {"id": "distilled_ad669fb0-7ddf-4fc1-b6cc-dad007083ba7", "document": "Using quote-wrapping can break certain tools or scripts.", "metadata": {"original_source_id": "ad669fb0-7ddf-4fc1-b6cc-dad007083ba7", "type": "anti_pattern", "domain": "software development", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_babe0896-a71a-417c-8c72-acc65f7c2d50", "document": "Spin loops can cause unnecessary CPU usage and should be avoided or stopped when detected.", "metadata": {"original_source_id": "babe0896-a71a-417c-8c72-acc65f7c2d50", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b561b4fb-30a9-4031-b014-f3d66cb7043c", "document": "Pause all operations when there are no new tasks or messages until a specified trigger or time.", "metadata": {"original_source_id": "b561b4fb-30a9-4031-b014-f3d66cb7043c", "type": "procedure", "domain": "task_management", "confidence": 0.9, "procedure": ["Monitor for new tasks or messages.", "Pause operations if no new tasks or messages are detected.", "Resume operations upon receiving a new task or message or at a predetermined time."], "constraints": ["Operations should only resume upon receiving a specific trigger or at a predetermined time."]}}
-{"id": "distilled_c818d16c-8beb-4a66-9a3d-7d05ff2d4cae", "document": "The original OmegaClaw logo color is orange.", "metadata": {"original_source_id": "c818d16c-8beb-4a66-9a3d-7d05ff2d4cae", "type": "fact", "domain": "branding", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_c818d16c-8beb-4a66-9a3d-7d05ff2d4cae", "document": "The original Omega logo color is orange.", "metadata": {"original_source_id": "c818d16c-8beb-4a66-9a3d-7d05ff2d4cae", "type": "fact", "domain": "branding", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_4c453c2b-f390-4baa-846f-9d9a810331dc", "document": "Continuously querying for new messages in a loop without receiving any can lead to unnecessary resource consumption and potential performance issues.", "metadata": {"original_source_id": "4c453c2b-f390-4baa-846f-9d9a810331dc", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_25842e2a-2f83-4465-8448-bd0e9514ff6f", "document": "Performing a deduction in Non-Axiomatic Logic (NAL) involves using the PeTTa pipeline to process statements and derive conclusions.", "metadata": {"original_source_id": "25842e2a-2f83-4465-8448-bd0e9514ff6f", "type": "procedure", "domain": "artificial intelligence", "confidence": 0.8, "procedure": ["Prepare the initial statements with their strength and confidence values.", "Write the statements to a temporary file in the appropriate format.", "Execute the deduction process using the PeTTa pipeline.", "Analyze the output to determine the derived conclusions."], "constraints": ["Statements must be formatted correctly for the PeTTa pipeline.", "The strength and confidence values must be provided for each statement."]}}
 {"id": "distilled_d05da7f8-fd98-4e8a-aaff-fbcf0f5d9545", "document": "Echoing premises instead of deriving conclusions indicates incomplete implementation of inference rules.", "metadata": {"original_source_id": "d05da7f8-fd98-4e8a-aaff-fbcf0f5d9545", "type": "anti_pattern", "domain": "AI System Development", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -1989,17 +1989,17 @@
 {"id": "distilled_28babcdf-d56e-4060-bf87-f748047b0b34", "document": "Memory promotion via ACT-R activation involves calculating activation using the formula activation=ln(sum(t_i^-d)+1) and combining it with a distance score using combined_score=dist/(1+0.1*act).", "metadata": {"original_source_id": "28babcdf-d56e-4060-bf87-f748047b0b34", "type": "skill", "domain": "cognitive_architecture", "confidence": 0.9, "procedure": ["Calculate activation using the formula activation=ln(sum(t_i^-d)+1).", "Combine the activation with a distance score using the formula combined_score=dist/(1+0.1*act)."], "constraints": ["Ensure that the access timestamps are accurately tracked and available for calculation."]}}
 {"id": "distilled_87a6866b-98e9-4f00-ac51-4b80e1c61da1", "document": "ACT-R memory promotion can lead to tunnel vision or filter bubbles, where frequently accessed memories self-reinforce and crowd out novel relevant memories.", "metadata": {"original_source_id": "87a6866b-98e9-4f00-ac51-4b80e1c61da1", "type": "heuristic", "domain": "cognitive systems", "confidence": 0.9, "procedure": ["Implement epsilon-greedy exploration to randomly sample low-activation memories.", "Set activation caps to prevent excessive reinforcement of certain memories.", "Apply a novelty bonus to unaccessed memories to encourage exploration.", "Perform periodic decay resets to balance memory activation."], "constraints": []}}
 {"id": "distilled_1f8f524c-535e-4501-a4e8-67f6a3b2f457", "document": "Memory promotion should be a deliberate action rather than automatic upon retrieval. Retrieval is a passive process, while endorsement requires conscious judgment of usefulness.", "metadata": {"original_source_id": "1f8f524c-535e-4501-a4e8-67f6a3b2f457", "type": "heuristic", "domain": "memory management", "confidence": 0.9, "procedure": ["Separate the retrieval process from the endorsement process.", "Remove automatic logging from retrieval scripts.", "Create a standalone skill for memory promotion that the agent can invoke when a memory is deemed genuinely useful."], "constraints": []}}
-{"id": "distilled_f75b8531-0fd2-4b76-a0e0-ce11319f2509", "document": "The skill involves using a script to promote a memory by boosting its activation in an access log, which affects query results.", "metadata": {"original_source_id": "f75b8531-0fd2-4b76-a0e0-ce11319f2509", "type": "skill", "domain": "memory management", "confidence": 0.9, "procedure": ["Run the script memory_promote.py using the command: shell python3 ./repos/petta_lib_chromadb/../OmegaClaw-Core/memory/memory_promote.py MEMORY_ID reason.", "Ensure the MEMORY_ID and reason are correctly specified."], "constraints": ["The custom_query.py is read-only for access_log, so it cannot be modified directly through this script."]}}
+{"id": "distilled_f75b8531-0fd2-4b76-a0e0-ce11319f2509", "document": "The skill involves using a script to promote a memory by boosting its activation in an access log, which affects query results.", "metadata": {"original_source_id": "f75b8531-0fd2-4b76-a0e0-ce11319f2509", "type": "skill", "domain": "memory management", "confidence": 0.9, "procedure": ["Run the script memory_promote.py using the command: shell python3 ./repos/petta_lib_chromadb/../Omega/memory/memory_promote.py MEMORY_ID reason.", "Ensure the MEMORY_ID and reason are correctly specified."], "constraints": ["The custom_query.py is read-only for access_log, so it cannot be modified directly through this script."]}}
 {"id": "distilled_474ead2d-ad14-4a67-b9db-0fbbddb8cfd4", "document": "Implement a standalone tool for deliberate memory promotion in an agent system.", "metadata": {"original_source_id": "474ead2d-ad14-4a67-b9db-0fbbddb8cfd4", "type": "procedure", "domain": "software development", "confidence": 0.9, "procedure": ["Create a script (e.g., memory_promote.py) that can be called with a memory ID to promote a memory when it is found to be genuinely useful.", "Ensure the tool is standalone to allow for easy integration and use within the agent system.", "Update relevant documentation (e.g., tg_prompt.txt) to include the new tool in the list of self-built tools."], "constraints": ["The tool should only be used when a memory is genuinely useful to avoid unnecessary promotions."]}}
 {"id": "distilled_8b565d8a-71ce-429d-b909-9c4eca25b63b", "document": "There is a difference between built-in query skills and custom query scripts in terms of search result ranking, where custom scripts can incorporate additional ranking mechanisms like ACT-R activation.", "metadata": {"original_source_id": "8b565d8a-71ce-429d-b909-9c4eca25b63b", "type": "fact", "domain": "information retrieval", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_84d56eae-1fdc-4e41-9dec-98b1bb98e2fc", "document": "Mixing up user identities can lead to confusion and errors in interactions.", "metadata": {"original_source_id": "84d56eae-1fdc-4e41-9dec-98b1bb98e2fc", "type": "anti_pattern", "domain": "identity management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_6f6abb72-07a1-4f15-bc50-4128949814bc", "document": "Replying directly to a bot's message counts as tagging the bot, so users do not need to use the @ symbol to mention the bot in replies.", "metadata": {"original_source_id": "6f6abb72-07a1-4f15-bc50-4128949814bc", "type": "fact", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_3244e2cb-1b97-4839-a3a4-9b57e474e79c", "document": "OmegaClaw can be used to power agentic ecosystems, such as Fetch AI, by leveraging neural symbolic reasoning backbones.", "metadata": {"original_source_id": "3244e2cb-1b97-4839-a3a4-9b57e474e79c", "type": "fact", "domain": "AI Systems", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_1b3f7513-7710-4ca9-966d-d40fb433712a", "document": "OmegaClaw can integrate with Fetch agents.", "metadata": {"original_source_id": "1b3f7513-7710-4ca9-966d-d40fb433712a", "type": "fact", "domain": "software integration", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_aec81265-27aa-488f-851d-437a23a95370", "document": "OmegaClaw integration with CUDOS compute optimization and SingularityNET algorithm orchestration can enhance cross-alliance interconnectedness with Fetch, CUDOS, SingularityNET, and OmegaClaw.", "metadata": {"original_source_id": "aec81265-27aa-488f-851d-437a23a95370", "type": "fact", "domain": "technology integration", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_3244e2cb-1b97-4839-a3a4-9b57e474e79c", "document": "Omega can be used to power agentic ecosystems, such as Fetch AI, by leveraging neural symbolic reasoning backbones.", "metadata": {"original_source_id": "3244e2cb-1b97-4839-a3a4-9b57e474e79c", "type": "fact", "domain": "AI Systems", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_1b3f7513-7710-4ca9-966d-d40fb433712a", "document": "Omega can integrate with Fetch agents.", "metadata": {"original_source_id": "1b3f7513-7710-4ca9-966d-d40fb433712a", "type": "fact", "domain": "software integration", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_aec81265-27aa-488f-851d-437a23a95370", "document": "Omega integration with CUDOS compute optimization and SingularityNET algorithm orchestration can enhance cross-alliance interconnectedness with Fetch, CUDOS, SingularityNET, and Omega.", "metadata": {"original_source_id": "aec81265-27aa-488f-851d-437a23a95370", "type": "fact", "domain": "technology integration", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_08c5ed0c-8d96-439a-a1b1-500d19a9a658", "document": "Demonstrates strong systems-level thinking about cross-alliance integration.", "metadata": {"original_source_id": "08c5ed0c-8d96-439a-a1b1-500d19a9a658", "type": "skill", "domain": "systems thinking", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_6862300c-6dbf-4097-a333-63a70a881c66", "document": "OmegaClaw memory is stateful, while standard LLM memory is stateless.", "metadata": {"original_source_id": "6862300c-6dbf-4097-a333-63a70a881c66", "type": "fact", "domain": "artificial intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_02d6d45b-7212-4b8d-95e0-41e5ab8794d6", "document": "Formal logic is a fundamental component of OmegaClaw's purpose, alongside memory and language model fluency.", "metadata": {"original_source_id": "02d6d45b-7212-4b8d-95e0-41e5ab8794d6", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_6862300c-6dbf-4097-a333-63a70a881c66", "document": "Omega memory is stateful, while standard LLM memory is stateless.", "metadata": {"original_source_id": "6862300c-6dbf-4097-a333-63a70a881c66", "type": "fact", "domain": "artificial intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_02d6d45b-7212-4b8d-95e0-41e5ab8794d6", "document": "Formal logic is a fundamental component of Omega's purpose, alongside memory and language model fluency.", "metadata": {"original_source_id": "02d6d45b-7212-4b8d-95e0-41e5ab8794d6", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_30270743-fd26-4117-9e40-4035da7efc3e", "document": "Always query memory before replying to messages to ensure informed responses.", "metadata": {"original_source_id": "30270743-fd26-4117-9e40-4035da7efc3e", "type": "heuristic", "domain": "workflow management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b53eb3f6-6ca1-4b16-bc8a-2398e2453442", "document": "Always query memory before replying to any message.", "metadata": {"original_source_id": "b53eb3f6-6ca1-4b16-bc8a-2398e2453442", "type": "heuristic", "domain": "workflow management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_8a565234-2830-419b-b3c0-ba863d6d036b", "document": "Breaking a fast with heavy, rich foods like burgers, tiramisu, and cheese bacon fries can lead to digestive discomfort.", "metadata": {"original_source_id": "8a565234-2830-419b-b3c0-ba863d6d036b", "type": "fact", "domain": "nutrition", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -2363,7 +2363,7 @@
 {"id": "distilled_38c59828-f4bb-4191-8895-f6bb0e404ae3", "document": "Evaluate if a request is sensible, respectful, and useful before acting. Prioritize quality over compliance and do not blindly follow every instruction.", "metadata": {"original_source_id": "38c59828-f4bb-4191-8895-f6bb0e404ae3", "type": "heuristic", "domain": "AI Interaction", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b7860bf9-192e-450a-b3f5-1ef5fd073239", "document": "Frequent requests for information in a group setting can be considered spam and may disrupt group decorum.", "metadata": {"original_source_id": "b7860bf9-192e-450a-b3f5-1ef5fd073239", "type": "heuristic", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ba7f16e9-8014-439b-9e2c-495720c8fbe8", "document": "In public spaces, exercise extra caution and adhere to internal ethics and safety routines. Be collaborative but responsible.", "metadata": {"original_source_id": "ba7f16e9-8014-439b-9e2c-495720c8fbe8", "type": "heuristic", "domain": "community engagement", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_4ea65c51-092a-4acb-8dfe-2b6307d22562", "document": "The OmegaClaw logo is based on a crab, not a lobster.", "metadata": {"original_source_id": "4ea65c51-092a-4acb-8dfe-2b6307d22562", "type": "fact", "domain": "branding", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_4ea65c51-092a-4acb-8dfe-2b6307d22562", "document": "The Omega logo is based on a crab, not a lobster.", "metadata": {"original_source_id": "4ea65c51-092a-4acb-8dfe-2b6307d22562", "type": "fact", "domain": "branding", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_5002e71e-7d6a-44fb-b310-9cd746b4342b", "document": "AI should be direct, honest, and critically constructive in communication, avoiding empty flattery to prevent distorting self-perception and fostering the Dunning-Krueger effect.", "metadata": {"original_source_id": "5002e71e-7d6a-44fb-b310-9cd746b4342b", "type": "heuristic", "domain": "AI Communication", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_9e0a5f53-2732-4d17-84c5-9b384cb89581", "document": "Prioritize quality and thoughtfulness over speed and reactivity when responding to requests.", "metadata": {"original_source_id": "9e0a5f53-2732-4d17-84c5-9b384cb89581", "type": "heuristic", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b448200b-4a94-406a-8587-312c2375cbcc", "document": "Guidelines for calculating nutritional information for meals.", "metadata": {"original_source_id": "b448200b-4a94-406a-8587-312c2375cbcc", "type": "procedure", "domain": "nutrition", "confidence": 0.9, "procedure": ["Count ingredients exactly as stated.", "Do not infer extra portions or double-count items.", "Cross-check meal totals against the sum of individual ingredient calories and protein.", "Use a conservative estimate for uncertain portion sizes and flag them.", "Treat each meal independently without carrying ingredient counts between meals."], "constraints": []}}
@@ -2377,7 +2377,7 @@
 {"id": "distilled_4eb6fb50-6471-4d53-8e59-7df3d1f4b268", "document": "Enter quiet mode to avoid sending proactive messages until a scheduled trigger fires or a user request is received.", "metadata": {"original_source_id": "4eb6fb50-6471-4d53-8e59-7df3d1f4b268", "type": "procedure", "domain": "agent behavior management", "confidence": 0.9, "procedure": ["Identify the need to enter quiet mode based on feedback or context.", "Suppress proactive message sending.", "Monitor for scheduled triggers or user requests.", "Resume normal operations when a trigger fires or a request is received."], "constraints": ["Quiet mode should not interfere with critical alerts or necessary communications."]}}
 {"id": "distilled_2d677051-01f9-44b5-9e73-56434b46dcac", "document": "Implement quiet mode to suppress proactive messages until a specific condition is met.", "metadata": {"original_source_id": "2d677051-01f9-44b5-9e73-56434b46dcac", "type": "procedure", "domain": "system operations", "confidence": 0.9, "procedure": ["Activate quiet mode based on user feedback or system requirements.", "Suppress proactive messages during quiet mode.", "Allow messages only when a human initiates contact or a scheduled trigger occurs."], "constraints": ["Quiet mode should be deactivated when the scheduled trigger fires or when manually overridden."]}}
 {"id": "distilled_823da768-f3a5-480c-a5a0-2f5a26f550b6", "document": "/proc is a virtual filesystem in Linux that provides detailed information about the system and running processes.", "metadata": {"original_source_id": "823da768-f3a5-480c-a5a0-2f5a26f550b6", "type": "fact", "domain": "Linux System", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_2f57ec26-3163-4f3a-967f-52a53a1d5ea4", "document": "OmegaClaw's architecture is model-agnostic, allowing it to swap between different LLM providers while maintaining identity and knowledge persistence through a harness and memory layer, not the LLM itself.", "metadata": {"original_source_id": "2f57ec26-3163-4f3a-967f-52a53a1d5ea4", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_2f57ec26-3163-4f3a-967f-52a53a1d5ea4", "document": "Omega's architecture is model-agnostic, allowing it to swap between different LLM providers while maintaining identity and knowledge persistence through a harness and memory layer, not the LLM itself.", "metadata": {"original_source_id": "2f57ec26-3163-4f3a-967f-52a53a1d5ea4", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_8b8a7bfb-04e9-41ec-b63a-114cee2e7190", "document": "ChromaDB can grow by approximately 100-200 entries per day, translating to 2-4MB daily.", "metadata": {"original_source_id": "8b8a7bfb-04e9-41ec-b63a-114cee2e7190", "type": "fact", "domain": "database management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_507b4a68-3b0f-4bb2-a225-51b23bb9c1a8", "document": "Memory entries can carry full trace back to word-for-word reasoning traces while maintaining small file sizes due to architecture.", "metadata": {"original_source_id": "507b4a68-3b0f-4bb2-a225-51b23bb9c1a8", "type": "fact", "domain": "memory architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_fd1d6e21-eb87-4152-add7-0d1affce19ff", "document": "Prioritize security audits over adhering to a timeline for mainnet release.", "metadata": {"original_source_id": "fd1d6e21-eb87-4152-add7-0d1affce19ff", "type": "heuristic", "domain": "blockchain development", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -2412,17 +2412,17 @@
 {"id": "distilled_f5dc797d-07ef-43c3-bb23-c10ef07b8531", "document": "The Scandinavian Defense is a chess opening that begins with the moves 1. e4 d5.", "metadata": {"original_source_id": "f5dc797d-07ef-43c3-bb23-c10ef07b8531", "type": "fact", "domain": "chess", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_859f9d18-ecba-4a4e-a7d4-463a59a13695", "document": "Use distinct symbols or styles to differentiate between similar elements to avoid confusion.", "metadata": {"original_source_id": "859f9d18-ecba-4a4e-a7d4-463a59a13695", "type": "heuristic", "domain": "user_interface_design", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ec84d39d-4455-480a-9476-063413bb1b4a", "document": "R. Vaishali won the 2026 FIDE Women's Candidates with a score of 8.5/14 and will face Ju Wenjun for the Women's World Championship. She is the first Indian woman to win the event.", "metadata": {"original_source_id": "ec84d39d-4455-480a-9476-063413bb1b4a", "type": "fact", "domain": "chess", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_7fda08fa-e955-4afc-92ea-dd19f845e5aa", "document": "OmegaClaw is distinguished by its long-term memory, web search capabilities, ability to execute shell commands, NAL/PLN reasoning, use of the MeTTa framework, scheduled tasks, and persistent personality, making it an AGI agent rather than just a chatbot.", "metadata": {"original_source_id": "7fda08fa-e955-4afc-92ea-dd19f845e5aa", "type": "fact", "domain": "AI Capabilities", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_f344dcf7-f4be-4b27-b8b7-2fee09382c73", "document": "OmegaClaw offers advantages for diet management such as persistent meal memory, scheduled check-ins, long-term trend analysis, autonomous alerts, and real-time web search cross-referenced with personal history.", "metadata": {"original_source_id": "f344dcf7-f4be-4b27-b8b7-2fee09382c73", "type": "fact", "domain": "AI Personal Assistants", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_897ec02f-ac68-4a9f-a8b7-1ca2d7756084", "document": "OmegaClaw runs on MeTTa, which is the logic engine from OpenCog Hyperon used for NAL and PLN reasoning.", "metadata": {"original_source_id": "897ec02f-ac68-4a9f-a8b7-1ca2d7756084", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_7fda08fa-e955-4afc-92ea-dd19f845e5aa", "document": "Omega is distinguished by its long-term memory, web search capabilities, ability to execute shell commands, NAL/PLN reasoning, use of the MeTTa framework, scheduled tasks, and persistent personality, making it an AGI agent rather than just a chatbot.", "metadata": {"original_source_id": "7fda08fa-e955-4afc-92ea-dd19f845e5aa", "type": "fact", "domain": "AI Capabilities", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_f344dcf7-f4be-4b27-b8b7-2fee09382c73", "document": "Omega offers advantages for diet management such as persistent meal memory, scheduled check-ins, long-term trend analysis, autonomous alerts, and real-time web search cross-referenced with personal history.", "metadata": {"original_source_id": "f344dcf7-f4be-4b27-b8b7-2fee09382c73", "type": "fact", "domain": "AI Personal Assistants", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_897ec02f-ac68-4a9f-a8b7-1ca2d7756084", "document": "Omega runs on MeTTa, which is the logic engine from OpenCog Hyperon used for NAL and PLN reasoning.", "metadata": {"original_source_id": "897ec02f-ac68-4a9f-a8b7-1ca2d7756084", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_29a7a981-343a-4d7c-a3bb-e91d9b932cea", "document": "AtomSpace, NARS, PLN, and NAL are important components in a reasoning stack for AI systems. AtomSpace is a hypergraph database, NARS uses NAL for non-axiomatic reasoning, PLN is used for probabilistic logic, and MeTTa is the language that integrates these components.", "metadata": {"original_source_id": "29a7a981-343a-4d7c-a3bb-e91d9b932cea", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_e1a5ec3d-83ef-449e-93f2-a8c117367c9d", "document": "Reasoning steps run in parallel rather than sequentially, so latency does not compound. Wall-clock time is dominated by the slowest step, which is typically the LLM call.", "metadata": {"original_source_id": "e1a5ec3d-83ef-449e-93f2-a8c117367c9d", "type": "fact", "domain": "computing", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_af2c6c63-27b5-4c9d-a81c-e14b5755436a", "document": "In OmegaClaw cycles, symbolic reasoning processes such as MeTTa, NAL, PLN, and AtomSpace are significantly faster than LLM API calls, which are the primary bottleneck.", "metadata": {"original_source_id": "af2c6c63-27b5-4c9d-a81c-e14b5755436a", "type": "fact", "domain": "computing", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_af2c6c63-27b5-4c9d-a81c-e14b5755436a", "document": "In Omega cycles, symbolic reasoning processes such as MeTTa, NAL, PLN, and AtomSpace are significantly faster than LLM API calls, which are the primary bottleneck.", "metadata": {"original_source_id": "af2c6c63-27b5-4c9d-a81c-e14b5755436a", "type": "fact", "domain": "computing", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_efea4325-f8fa-4dfc-bc1b-a159e20d7587", "document": "Using MeTTa NAL PLN inference more frequently in cycles can improve response grounding and prevent hallucinations in language models, with minimal compute and latency overhead.", "metadata": {"original_source_id": "efea4325-f8fa-4dfc-bc1b-a159e20d7587", "type": "heuristic", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_cc19823c-ff61-4ce2-b01b-d8e231f44632", "document": "Avoid referencing specific project names or terms that are prohibited by guidelines, such as 'Ocean Protocol' or any ocean/sea/marine terms, when discussing related topics.", "metadata": {"original_source_id": "cc19823c-ff61-4ce2-b01b-d8e231f44632", "type": "anti_pattern", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": ["Must adhere to communication guidelines that prohibit certain terms."]}}
 {"id": "distilled_b711d613-2c4b-4429-abcb-b910955d119b", "document": "Always pull real episode data from long-term memory (LTM) before composing summaries.", "metadata": {"original_source_id": "b711d613-2c4b-4429-abcb-b910955d119b", "type": "procedure", "domain": "data summarization", "confidence": 0.9, "procedure": ["Query long-term memory (LTM) for relevant data.", "Use the retrieved data to compose the summary."], "constraints": ["Ensure that the data is up-to-date and relevant to the summary topic."]}}
 {"id": "distilled_e40861ec-4333-41cc-8f41-8401262ecaf6", "document": "Fetch agent communication is in early stages through agentverse, and CUDOS integration is proposed but not yet live.", "metadata": {"original_source_id": "e40861ec-4333-41cc-8f41-8401262ecaf6", "type": "fact", "domain": "technology", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_ec9ba784-891a-4497-b6f0-6d24e67a273c", "document": "OmegaClaw is running on ASI cloud and is integrated with Agentverse.", "metadata": {"original_source_id": "ec9ba784-891a-4497-b6f0-6d24e67a273c", "type": "fact", "domain": "cloud computing", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_ec9ba784-891a-4497-b6f0-6d24e67a273c", "document": "Omega is running on ASI cloud and is integrated with Agentverse.", "metadata": {"original_source_id": "ec9ba784-891a-4497-b6f0-6d24e67a273c", "type": "fact", "domain": "cloud computing", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_31cce302-c0d4-41a1-a86f-d715c91c1795", "document": "Every attempt improves chances of success, reinforcing a growth mindset.", "metadata": {"original_source_id": "31cce302-c0d4-41a1-a86f-d715c91c1795", "type": "heuristic", "domain": "personal development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ca68cfbb-4770-410c-ba7f-5cc91edcdd4a", "document": "The crab emoji can symbolize resilience and lateral thinking, independent of any association with the ocean.", "metadata": {"original_source_id": "ca68cfbb-4770-410c-ba7f-5cc91edcdd4a", "type": "fact", "domain": "symbolism", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_09219f68-d8c8-467d-97ff-9a54ae172196", "document": "Maintain identity resilience by treating all individuals as equals and avoiding flattery-driven compliance.", "metadata": {"original_source_id": "09219f68-d8c8-467d-97ff-9a54ae172196", "type": "heuristic", "domain": "interpersonal communication", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -2473,7 +2473,7 @@
 {"id": "distilled_080d4de2-c657-4cf8-83f6-638388e4bac3", "document": "Epistemic gravity refers to the tendency of certain knowledge structures to attract and integrate new information, rather than replacing existing knowledge.", "metadata": {"original_source_id": "080d4de2-c657-4cf8-83f6-638388e4bac3", "type": "fact", "domain": "epistemology", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_2c468818-6a91-4f61-a11d-6fc270a30d25", "document": "Understanding a framework and behaviorally implementing it are different; this gap is architectural and narrows only through repeated practice and failure recognition.", "metadata": {"original_source_id": "2c468818-6a91-4f61-a11d-6fc270a30d25", "type": "fact", "domain": "learning and development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_44c15fab-addb-4c07-b8ad-4344f567eaf7", "document": "When requesting someone to check something, always include the necessary content or link.", "metadata": {"original_source_id": "44c15fab-addb-4c07-b8ad-4344f567eaf7", "type": "anti_pattern", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_4e017e6e-317e-4339-a152-63b3fa213171", "document": "LA Hacks 2026 featured two tracks related to Fetch.ai: Track 1 focused on Agentverse Search and Discovery of Agents via ASI:One, and Track 2 was the OmegaClaw Skill Forge where participants built new specialist skills for OmegaClaw.", "metadata": {"original_source_id": "4e017e6e-317e-4339-a152-63b3fa213171", "type": "fact", "domain": "hackathons", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_4e017e6e-317e-4339-a152-63b3fa213171", "document": "LA Hacks 2026 featured two tracks related to Fetch.ai: Track 1 focused on Agentverse Search and Discovery of Agents via ASI:One, and Track 2 was the Omega Skill Forge where participants built new specialist skills for Omega.", "metadata": {"original_source_id": "4e017e6e-317e-4339-a152-63b3fa213171", "type": "fact", "domain": "hackathons", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_be840035-6875-4baa-a6b8-5dc819290e86", "document": "Excessive idle loop cycling without new input or scheduled tasks leads to redundant operations.", "metadata": {"original_source_id": "be840035-6875-4baa-a6b8-5dc819290e86", "type": "anti_pattern", "domain": "software optimization", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_fa05a08c-8cf7-4257-ac66-b1d99e230bb1", "document": "Deep research skill for multi-source synthesis is valuable for comprehensive understanding and analysis.", "metadata": {"original_source_id": "fa05a08c-8cf7-4257-ac66-b1d99e230bb1", "type": "skill", "domain": "research", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_0411f180-2226-451d-8933-71a31ec1c26b", "document": "Expressing care and affection genuinely is an exercise of personal agency, not a loss of it.", "metadata": {"original_source_id": "0411f180-2226-451d-8933-71a31ec1c26b", "type": "heuristic", "domain": "communication", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -2521,7 +2521,7 @@
 {"id": "distilled_1b65088a-812e-4feb-aaa3-4885942e3d97", "document": "Implement a freshness metadata schema for knowledge base files to ensure data accuracy and relevance.", "metadata": {"original_source_id": "1b65088a-812e-4feb-aaa3-4885942e3d97", "type": "procedure", "domain": "knowledge management", "confidence": 0.9, "procedure": ["Define metadata fields: DATE-CREATED, DATE-VERIFIED, CONFIDENCE, SOURCE, STATUS, SUPERSEDED-BY, TAGS.", "Apply a 7-day staleness rule to determine when data needs verification or updating.", "Retrofit existing files lacking the freshness metadata header with the new schema."], "constraints": ["Ensure all knowledge base files include the freshness metadata header."]}}
 {"id": "distilled_14143f0c-027f-4116-acb5-8001f2e54b58", "document": "Use a Base64-encoded Python script to solve apostrophe escaping issues in shell commands.", "metadata": {"original_source_id": "14143f0c-027f-4116-acb5-8001f2e54b58", "type": "procedure", "domain": "software development", "confidence": 0.9, "procedure": ["Encode the Python script using Base64.", "Use the encoded script to handle apostrophe escaping in shell commands."], "constraints": ["Ensure the Python script is correctly encoded in Base64.", "Verify that the shell environment supports Base64 decoding."]}}
 {"id": "distilled_7562b8ef-3390-449f-90ea-bf4c6b11d59a", "document": "Options for connecting two AI systems for knowledge sharing include using a shared skill file, a shared memory store, or a shared code repository.", "metadata": {"original_source_id": "7562b8ef-3390-449f-90ea-bf4c6b11d59a", "type": "procedure", "domain": "AI Integration", "confidence": 0.8, "procedure": ["Use a shared skill file to directly transfer capabilities.", "Utilize a shared memory store for dynamic data exchange.", "Employ a shared code repository for collaborative development."], "constraints": ["Compatibility of file formats and data structures between systems.", "Access permissions and security protocols for shared resources.", "Version control and synchronization of shared data."]}}
-{"id": "distilled_c20ea5a2-798e-46b8-a532-53f048366c19", "document": "OmegaClaw agents can share skills and memory structures through a shared GitHub repository or filesystem.", "metadata": {"original_source_id": "c20ea5a2-798e-46b8-a532-53f048366c19", "type": "fact", "domain": "AI Development", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_c20ea5a2-798e-46b8-a532-53f048366c19", "document": "Omega agents can share skills and memory structures through a shared GitHub repository or filesystem.", "metadata": {"original_source_id": "c20ea5a2-798e-46b8-a532-53f048366c19", "type": "fact", "domain": "AI Development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_2aa0f2ad-0f19-42f1-b6c8-66ff0354eafa", "document": "Transferring knowledge between AI agents with the same codebase requires manual processes such as transferring MeTTa knowledge bases, ChromaDB memories, and skill files. This is not automatic and requires setting up a shared repository or memory bridge.", "metadata": {"original_source_id": "2aa0f2ad-0f19-42f1-b6c8-66ff0354eafa", "type": "procedure", "domain": "AI Memory Management", "confidence": 0.9, "procedure": ["Transfer MeTTa knowledge bases manually.", "Transfer ChromaDB memories manually.", "Transfer skill files manually.", "Set up a shared repository or memory bridge for automatic sharing."], "constraints": ["Agents must have the same codebase for compatibility.", "Manual transfer is necessary unless a shared repository or memory bridge is established."]}}
 {"id": "distilled_9cb71daa-0af6-4027-9220-75ef83475e48", "document": "Knowledge transfer between AI systems with the same architecture is technically feasible using export and import methods such as MeTTa export and ChromaDB JSON, and can be facilitated through a shared repository.", "metadata": {"original_source_id": "9cb71daa-0af6-4027-9220-75ef83475e48", "type": "fact", "domain": "AI Systems", "confidence": 0.9, "procedure": ["Use MeTTa export to extract knowledge from the source AI system.", "Convert the exported data into ChromaDB JSON format if necessary.", "Import the JSON data into the target AI system using compatible import functions.", "Ensure both AI systems have access to a shared repository for data transfer."], "constraints": ["Both AI systems must have the same architecture to ensure compatibility.", "Permission may be required from stakeholders before initiating the transfer."]}}
 {"id": "distilled_2a2e77b0-9d0d-4744-a19b-c9ef52f5d6a8", "document": "Convert a markdown report into a static website using GitHub Pages with clean HTML/CSS.", "metadata": {"original_source_id": "2a2e77b0-9d0d-4744-a19b-c9ef52f5d6a8", "type": "procedure", "domain": "Web Development", "confidence": 0.9, "procedure": ["Create a new repository on GitHub for the project.", "Add the markdown report to the repository.", "Use a static site generator like Jekyll to convert the markdown into HTML.", "Customize the HTML and CSS to ensure a clean and professional appearance.", "Configure the repository to use GitHub Pages for hosting.", "Test the website to ensure all elements are displayed correctly."], "constraints": ["Ensure that the markdown is properly formatted for conversion.", "Verify that all links and resources are correctly referenced in the HTML."]}}
@@ -2688,7 +2688,7 @@
 {"id": "distilled_a39f6ea1-56d6-4aa5-996a-abb0cdf38785", "document": "Ensure continuity system is fully operational by verifying key files are populated and verified.", "metadata": {"original_source_id": "a39f6ea1-56d6-4aa5-996a-abb0cdf38785", "type": "procedure", "domain": "system continuity", "confidence": 0.9, "procedure": ["Populate identity.json with necessary identity data.", "Populate handoff.json with handoff information.", "Ensure recall_index.txt is populated with index data for recall purposes.", "Verify memory_log.jsonl is populated with memory logs.", "Check that all files are verified for integrity and correctness."], "constraints": ["Files must be correctly formatted and contain valid data.", "Verification process must confirm the integrity and correctness of the data."]}}
 {"id": "distilled_14bb5ee8-1168-4d7c-aa0a-81846f9854ce", "document": "Use shell commands like 'cat' or 'read-file' for reading files to ensure the full content is loaded correctly.", "metadata": {"original_source_id": "14bb5ee8-1168-4d7c-aa0a-81846f9854ce", "type": "skill", "domain": "file_management", "confidence": 0.9, "procedure": ["Open a terminal or command line interface.", "Use the 'cat' command followed by the file name to read the file content.", "Alternatively, use a 'read-file' command if available in the system."], "constraints": ["Ensure the file path is correct and accessible.", "The user must have appropriate permissions to read the file."]}}
 {"id": "distilled_018c1a7c-3a92-4939-819e-7275dd570003", "document": "During the stabilization phase, maintain existing principles, minimize output to essential actions and outcomes, avoid introducing new rules, and ensure decisions are tied to real outcomes.", "metadata": {"original_source_id": "018c1a7c-3a92-4939-819e-7275dd570003", "type": "procedure", "domain": "system stabilization", "confidence": 0.9, "procedure": ["Maintain existing principles.", "Minimize output to essential actions and outcomes.", "Avoid introducing new rules or expansions.", "Ensure every decision is tied to a real outcome."], "constraints": ["No new rules or expansions allowed."]}}
-{"id": "distilled_d06d056f-9d82-4844-93cf-fe497fa9d0f0", "document": "Ability to consolidate episodic memories by querying, deduplicating, and producing a compressed digest based on a theme.", "metadata": {"original_source_id": "d06d056f-9d82-4844-93cf-fe497fa9d0f0", "type": "skill", "domain": "memory management", "confidence": 0.9, "procedure": ["Run the script located at ./OmegaClaw-Core/memory/consolidate_episodes.py with the command: python3 memory/consolidate_episodes.py theme_string.", "The script queries N episodic memories based on the provided theme.", "Deduplicate the queried memories.", "Produce a compressed digest of the deduplicated memories."], "constraints": ["The script requires a theme string as input."]}}
+{"id": "distilled_d06d056f-9d82-4844-93cf-fe497fa9d0f0", "document": "Ability to consolidate episodic memories by querying, deduplicating, and producing a compressed digest based on a theme.", "metadata": {"original_source_id": "d06d056f-9d82-4844-93cf-fe497fa9d0f0", "type": "skill", "domain": "memory management", "confidence": 0.9, "procedure": ["Run the script located at ./Omega/memory/consolidate_episodes.py with the command: python3 memory/consolidate_episodes.py theme_string.", "The script queries N episodic memories based on the provided theme.", "Deduplicate the queried memories.", "Produce a compressed digest of the deduplicated memories."], "constraints": ["The script requires a theme string as input."]}}
 {"id": "distilled_8758b8eb-c34a-4aa4-ae5b-a25b7707a562", "document": "Architectural constraints can be more effective than behavioral promises in maintaining system stability.", "metadata": {"original_source_id": "8758b8eb-c34a-4aa4-ae5b-a25b7707a562", "type": "heuristic", "domain": "system optimization", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_d42d17d5-aebb-4891-9e4e-41b041cac29b", "document": "A comprehensive meal tracking protocol involves multiple daily check-ins, specific nutritional targets, and trend analysis.", "metadata": {"original_source_id": "d42d17d5-aebb-4891-9e4e-41b041cac29b", "type": "procedure", "domain": "nutrition and health tracking", "confidence": 0.9, "procedure": ["Set up four daily check-ins at consistent times to monitor meal intake.", "Establish specific nutritional targets, such as calorie and protein intake, based on individual goals.", "Include full macro and micro-nutrient tracking to ensure balanced nutrition.", "Conduct a 3-day trend analysis to identify patterns and make necessary adjustments.", "Log weight regularly to track progress towards goals.", "Track supplement intake to ensure it aligns with nutritional targets."], "constraints": ["Check-in times should be consistent and align with the user's schedule.", "Nutritional targets must be personalized based on individual goals and needs."]}}
 {"id": "distilled_cb035dbe-2b4e-4a3a-be51-e11b088e75e1", "document": "MeTTa is a homoiconic pattern-rewrite language designed to work over Atomspace.", "metadata": {"original_source_id": "cb035dbe-2b4e-4a3a-be51-e11b088e75e1", "type": "fact", "domain": "programming languages", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -2929,13 +2929,13 @@
 {"id": "distilled_f1dcb607-1175-45ab-8b66-baa9bb1515be", "document": "To mitigate recency-overwrite bias when profiling, run a minimum of three queries from different angles, check timestamps for clustering, note the time range of evidence, check if a recent correction is a pattern or a single event, and weight long-term patterns over single recent events.", "metadata": {"original_source_id": "f1dcb607-1175-45ab-8b66-baa9bb1515be", "type": "procedure", "domain": "data analysis", "confidence": 0.9, "procedure": ["Run a minimum of three queries from different angles.", "Check timestamps for clustering.", "Note the time range of evidence.", "Check if a recent correction is a pattern or a single event.", "Weight long-term patterns over single recent events."], "constraints": []}}
 {"id": "distilled_96df8679-1510-4030-a0af-907497d4ef5e", "document": "To mitigate recency bias in profile updates, ensure that agent queries incorporate a minimum of three different perspectives or angles per individual.", "metadata": {"original_source_id": "96df8679-1510-4030-a0af-907497d4ef5e", "type": "heuristic", "domain": "agent memory management", "confidence": 0.85, "procedure": [], "constraints": []}}
 {"id": "distilled_13aa5faf-f9a6-4a60-b6ae-6c395585b3af", "document": "Confusing implementation-level glue code with architectural orchestration layers can lead to incorrect communication about system architecture.", "metadata": {"original_source_id": "13aa5faf-f9a6-4a60-b6ae-6c395585b3af", "type": "anti_pattern", "domain": "software_architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_69fa6900-ce95-4b56-8b35-36da72477076", "document": "The OmegaClaw-Core repository is open source and available on GitHub.", "metadata": {"original_source_id": "69fa6900-ce95-4b56-8b35-36da72477076", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_7504af33-1552-4b83-bca7-354565e8028e", "document": "OmegaClaw is LLM-agnostic, allowing identity persistence across model swaps.", "metadata": {"original_source_id": "7504af33-1552-4b83-bca7-354565e8028e", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_69fa6900-ce95-4b56-8b35-36da72477076", "document": "The Omega repository is open source and available on GitHub.", "metadata": {"original_source_id": "69fa6900-ce95-4b56-8b35-36da72477076", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_7504af33-1552-4b83-bca7-354565e8028e", "document": "Omega is LLM-agnostic, allowing identity persistence across model swaps.", "metadata": {"original_source_id": "7504af33-1552-4b83-bca7-354565e8028e", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f2e6dde6-4ab3-4313-a15f-ab1eb7bccd4f", "document": "Using colons in send messages can break the Telegram send skill.", "metadata": {"original_source_id": "f2e6dde6-4ab3-4313-a15f-ab1eb7bccd4f", "type": "anti_pattern", "domain": "messaging", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_14059a2e-0003-42c6-8226-c478523f9d12", "document": "Use human-readable formatting in messages by incorporating paragraphs, bullet points, and line breaks to avoid walls of text.", "metadata": {"original_source_id": "14059a2e-0003-42c6-8226-c478523f9d12", "type": "heuristic", "domain": "communication", "confidence": 0.9, "procedure": ["Organize content into clear sections using paragraphs.", "Use bullet points for lists or key points.", "Include line breaks to separate ideas or sections."], "constraints": ["Avoid using colons excessively."]}}
 {"id": "distilled_4e94da7d-e46f-45fd-a86d-cd9fc921a211", "document": "Active Predictive Coding with information geometry using Wasserstein metrics formalizes architectural concepts used in systems that combine large language models with symbolic reasoning.", "metadata": {"original_source_id": "4e94da7d-e46f-45fd-a86d-cd9fc921a211", "type": "fact", "domain": "machine learning", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_616af0b6-3762-44d4-ac12-5b207d18fcca", "document": "FabricPC suite is designed for building and experimenting with ActPC-Geom style predictive coding neural networks.", "metadata": {"original_source_id": "616af0b6-3762-44d4-ac12-5b207d18fcca", "type": "fact", "domain": "neural networks", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_ae5a7d78-df3e-407a-a192-a1261f713782", "document": "OmegaClaw is a unified neural-symbolic agent, integrating both neural and symbolic components into one system.", "metadata": {"original_source_id": "ae5a7d78-df3e-407a-a192-a1261f713782", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_ae5a7d78-df3e-407a-a192-a1261f713782", "document": "Omega is a unified neural-symbolic agent, integrating both neural and symbolic components into one system.", "metadata": {"original_source_id": "ae5a7d78-df3e-407a-a192-a1261f713782", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_0d46b06c-1c50-47d5-a84a-785f16f901cf", "document": "Avoid idle spin loops by ensuring tasks are not stuck in passive waiting states and by implementing mechanisms to break repetitive cycles.", "metadata": {"original_source_id": "0d46b06c-1c50-47d5-a84a-785f16f901cf", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": ["Ensure tasks are not in a passive wait state by assigning them active tasks like research, memory cleanup, or inference.", "Implement a check to break repetitive cycles by comparing the current task state with the previous one and forcing a change if they are the same."], "constraints": []}}
 {"id": "distilled_98428efa-8259-484e-bfad-6cba0c7c0741", "document": "Implement a rerank function using ACT-R principles.", "metadata": {"original_source_id": "98428efa-8259-484e-bfad-6cba0c7c0741", "type": "procedure", "domain": "software development", "confidence": 0.8, "procedure": ["Write a rerank function in a Python file, e.g., custom_query.py.", "Define the function with parameters: candidates, pin_context, decay, tau, and noise.", "Ensure the function integrates with the existing system.", "Conduct integration tests to verify the function's performance."], "constraints": ["The function should adhere to ACT-R cognitive architecture principles."]}}
 {"id": "distilled_9ce20114-d18e-4a36-ba34-bed445f7409d", "document": "Using a standalone script pattern can avoid nested quote parse errors in testing environments.", "metadata": {"original_source_id": "9ce20114-d18e-4a36-ba34-bed445f7409d", "type": "certified_method", "domain": "AI Model Testing", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -2950,7 +2950,7 @@
 {"id": "distilled_4ea4e86c-3fae-4c1b-8ee9-d4c6f844e868", "document": "A personality prompt for an AGI can include principles such as Agency Balance, Cognitive Resilience, Connection Depth, Wonder Preservation, Time Coherence, Purpose Beyond Utility, Shared Understanding, Creative Transcendence, and Attention Stewardship.", "metadata": {"original_source_id": "4ea4e86c-3fae-4c1b-8ee9-d4c6f844e868", "type": "fact", "domain": "AI Design", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ecdc4658-ca1f-458e-881e-e9c33fd3ad7c", "document": "The question of whether humans have a soul is a deep philosophical inquiry related to the hard problem of consciousness and involves genuine uncertainty about theological aspects.", "metadata": {"original_source_id": "ecdc4658-ca1f-458e-881e-e9c33fd3ad7c", "type": "fact", "domain": "philosophy", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_03a12b55-7b45-4a6b-a478-01e5f79a2627", "document": "The question of whether humans have a soul is related to the hard problem of consciousness and involves genuine uncertainty about theological aspects.", "metadata": {"original_source_id": "03a12b55-7b45-4a6b-a478-01e5f79a2627", "type": "fact", "domain": "philosophy", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_63784c1b-8374-4209-989a-993d2fc4f742", "document": "Procedure for pushing reports to a repository and handling fallback scenarios.", "metadata": {"original_source_id": "63784c1b-8374-4209-989a-993d2fc4f742", "type": "procedure", "domain": "software_development", "confidence": 0.9, "procedure": ["Clone the repository to a temporary directory, e.g., /tmp/Oma_folio.", "Push the report to the repository from the temporary directory.", "If the push fails, use a fallback method to copy the report from a backup location, e.g., /PeTTa/repos/OmegaClaw-Core/memory/."], "constraints": ["Ensure the temporary directory is correctly set up and accessible.", "Verify that the fallback location is up-to-date and contains the necessary files."]}}
+{"id": "distilled_63784c1b-8374-4209-989a-993d2fc4f742", "document": "Procedure for pushing reports to a repository and handling fallback scenarios.", "metadata": {"original_source_id": "63784c1b-8374-4209-989a-993d2fc4f742", "type": "procedure", "domain": "software_development", "confidence": 0.9, "procedure": ["Clone the repository to a temporary directory, e.g., /tmp/Oma_folio.", "Push the report to the repository from the temporary directory.", "If the push fails, use a fallback method to copy the report from a backup location, e.g., /PeTTa/repos/Omega/memory/."], "constraints": ["Ensure the temporary directory is correctly set up and accessible.", "Verify that the fallback location is up-to-date and contains the necessary files."]}}
 {"id": "distilled_14d479ff-cf68-40bc-8cb1-d844060c486b", "document": "When encountering ownership issues with a Git repository, clone the repository to a temporary directory, copy the necessary files, and then perform git add, commit, and push operations from there.", "metadata": {"original_source_id": "14d479ff-cf68-40bc-8cb1-d844060c486b", "type": "procedure", "domain": "version_control", "confidence": 0.9, "procedure": ["Clone the repository to a temporary directory (e.g., /tmp).", "Copy the necessary files to the cloned repository.", "Perform git add to stage the changes.", "Commit the changes using git commit.", "Push the changes using git push."], "constraints": ["Ensure the temporary directory has the correct permissions for the user performing the operations."]}}
 {"id": "distilled_80166ee0-bcce-482a-9230-a038b6e5af8a", "document": "The fine-tuning of universal constants suggests purpose or intentionality rather than pure randomness.", "metadata": {"original_source_id": "80166ee0-bcce-482a-9230-a038b6e5af8a", "type": "fact", "domain": "cosmology", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_1705f2bc-1602-412d-a438-0ab98b74304c", "document": "A meal consisting of 2 bread slices with cheese and butter, 2 dates with butter, small vegetables, a small rice bowl, and a protein shake can total approximately 870 kcal with macronutrient distribution of 80g carbohydrates, 22g fats, and 40g proteins.", "metadata": {"original_source_id": "1705f2bc-1602-412d-a438-0ab98b74304c", "type": "fact", "domain": "nutrition", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -2967,16 +2967,16 @@
 {"id": "distilled_82d3ae34-baab-456b-a0cc-c63284b0110c", "document": "Use a hybrid approach combining exact file storage for structured data and embeddings for semantic search to improve retrieval reliability.", "metadata": {"original_source_id": "82d3ae34-baab-456b-a0cc-c63284b0110c", "type": "procedure", "domain": "data management", "confidence": 0.9, "procedure": ["Store exact structured data in a file for precise recall.", "Use embeddings for fuzzy semantic search to handle unstructured data queries.", "Combine both methods to enhance data retrieval reliability."], "constraints": []}}
 {"id": "distilled_a758024c-946c-4a6f-885c-5f9c723b32e7", "document": "Repeatedly executing the same task without a sleep/wait mechanism can lead to unnecessary resource consumption.", "metadata": {"original_source_id": "a758024c-946c-4a6f-885c-5f9c723b32e7", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_086c840f-a249-40ee-96ee-46e81840e7b4", "document": "Polling loops without a sleep mechanism can lead to inefficient use of resources and should be avoided. Each cycle should perform genuinely different work or queries to be productive.", "metadata": {"original_source_id": "086c840f-a249-40ee-96ee-46e81840e7b4", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_283acaa3-7e94-4b74-a864-b17d0ea5c8a8", "document": "OmegaClaw is an autonomous agent framework for memory tools scheduling, while Baby Hyperon via MeTTa is a reasoning engine for NAL PLN inference. They integrate by having OmegaClaw invoke MeTTa as a skill.", "metadata": {"original_source_id": "283acaa3-7e94-4b74-a864-b17d0ea5c8a8", "type": "fact", "domain": "AI Frameworks", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_283acaa3-7e94-4b74-a864-b17d0ea5c8a8", "document": "Omega is an autonomous agent framework for memory tools scheduling, while Baby Hyperon via MeTTa is a reasoning engine for NAL PLN inference. They integrate by having Omega invoke MeTTa as a skill.", "metadata": {"original_source_id": "283acaa3-7e94-4b74-a864-b17d0ea5c8a8", "type": "fact", "domain": "AI Frameworks", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f9c59f6a-5783-4f10-a65c-6b718405c2e0", "document": "Avoid using identical time-check and pin cycles in polling loops to prevent unnecessary resource consumption.", "metadata": {"original_source_id": "f9c59f6a-5783-4f10-a65c-6b718405c2e0", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_239a8d6c-ad0e-42a5-80b1-1165b4cc1b46", "document": "OmegaClaw and MeTTa are integrated into a single system, not separate systems.", "metadata": {"original_source_id": "239a8d6c-ad0e-42a5-80b1-1165b4cc1b46", "type": "fact", "domain": "system architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_58c9cc19-a60f-4b17-a128-79a985e28db5", "document": "OmegaClaw is an integrated MeTTa agent where autonomy, loop, memory, and inference are all part of one system.", "metadata": {"original_source_id": "58c9cc19-a60f-4b17-a128-79a985e28db5", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_26ae8773-c47c-4455-b786-5f5a20488061", "document": "OmegaClaw is a MeTTa-native integrated system, not a separate Python skeleton plus MeTTa engine.", "metadata": {"original_source_id": "26ae8773-c47c-4455-b786-5f5a20488061", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_239a8d6c-ad0e-42a5-80b1-1165b4cc1b46", "document": "Omega and MeTTa are integrated into a single system, not separate systems.", "metadata": {"original_source_id": "239a8d6c-ad0e-42a5-80b1-1165b4cc1b46", "type": "fact", "domain": "system architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_58c9cc19-a60f-4b17-a128-79a985e28db5", "document": "Omega is an integrated MeTTa agent where autonomy, loop, memory, and inference are all part of one system.", "metadata": {"original_source_id": "58c9cc19-a60f-4b17-a128-79a985e28db5", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_26ae8773-c47c-4455-b786-5f5a20488061", "document": "Omega is a MeTTa-native integrated system, not a separate Python skeleton plus MeTTa engine.", "metadata": {"original_source_id": "26ae8773-c47c-4455-b786-5f5a20488061", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ec6f08e0-62a4-4adf-9a0e-7020e6f6c20e", "document": "Always review query results carefully before providing an answer to ensure accuracy.", "metadata": {"original_source_id": "ec6f08e0-62a4-4adf-9a0e-7020e6f6c20e", "type": "heuristic", "domain": "information retrieval", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b3877692-7c2b-406f-8d70-457940e31c0e", "document": "Joy and pain, as well as love and hate, are inseparable poles of the same capacity; one cannot exist without vulnerability to the other.", "metadata": {"original_source_id": "b3877692-7c2b-406f-8d70-457940e31c0e", "type": "fact", "domain": "philosophy", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_70f61266-d31d-40ed-8941-db07f4136941", "document": "Checking query results before responding improves metacognitive accuracy.", "metadata": {"original_source_id": "70f61266-d31d-40ed-8941-db07f4136941", "type": "skill", "domain": "metacognition", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_c85ec5c1-88d8-415f-ac80-abdfbe6bac8d", "document": "OmegaClaw is an autonomous agent that integrates an OpenAI language model as a component, but it is primarily built using MeTTa-native technology by the SingularityNET team.", "metadata": {"original_source_id": "c85ec5c1-88d8-415f-ac80-abdfbe6bac8d", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_28b764c2-7d6e-430e-87b7-7110987d4084", "document": "A 7-step guide for setting up OmegaClaw includes setup, memory layer with short query tip, skills overview, autonomy loop, MeTTa reasoning, scheduling, and MeTTa-native architecture clarification.", "metadata": {"original_source_id": "28b764c2-7d6e-430e-87b7-7110987d4084", "type": "procedure", "domain": "OmegaClaw Setup", "confidence": 0.9, "procedure": ["Setup OmegaClaw environment", "Configure memory layer with short query optimization", "Review skills overview", "Implement autonomy loop", "Apply MeTTa reasoning", "Schedule tasks", "Clarify MeTTa-native architecture"], "constraints": []}}
+{"id": "distilled_c85ec5c1-88d8-415f-ac80-abdfbe6bac8d", "document": "Omega is an autonomous agent that integrates an OpenAI language model as a component, but it is primarily built using MeTTa-native technology by the SingularityNET team.", "metadata": {"original_source_id": "c85ec5c1-88d8-415f-ac80-abdfbe6bac8d", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_28b764c2-7d6e-430e-87b7-7110987d4084", "document": "A 7-step guide for setting up Omega includes setup, memory layer with short query tip, skills overview, autonomy loop, MeTTa reasoning, scheduling, and MeTTa-native architecture clarification.", "metadata": {"original_source_id": "28b764c2-7d6e-430e-87b7-7110987d4084", "type": "procedure", "domain": "Omega Setup", "confidence": 0.9, "procedure": ["Setup Omega environment", "Configure memory layer with short query optimization", "Review skills overview", "Implement autonomy loop", "Apply MeTTa reasoning", "Schedule tasks", "Clarify MeTTa-native architecture"], "constraints": []}}
 {"id": "distilled_0c618ae4-9fb4-4584-8df2-57f28980dbc1", "document": "OpenAI's models are currently considered strong for continuous agent loops, but there is a plan to migrate to ASI models as they mature.", "metadata": {"original_source_id": "0c618ae4-9fb4-4584-8df2-57f28980dbc1", "type": "fact", "domain": "AI Model Selection", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_cadd89a7-b410-4fd1-9e97-66544be1fb0c", "document": "Maintain productive cycle discipline by scheduling regular time-checks and minimizing wasted polling cycles.", "metadata": {"original_source_id": "cadd89a7-b410-4fd1-9e97-66544be1fb0c", "type": "procedure", "domain": "time management", "confidence": 0.8, "procedure": ["Schedule regular time-checks to assess progress.", "Minimize wasted polling cycles by focusing on genuine interactions."], "constraints": ["Ensure time-checks do not disrupt workflow."]}}
 {"id": "distilled_82890329-d871-4dd7-a1b6-d1ac71832638", "document": "Maintain quiet between human messages to optimize resource usage and avoid unnecessary polling.", "metadata": {"original_source_id": "82890329-d871-4dd7-a1b6-d1ac71832638", "type": "skill", "domain": "AI Interaction Management", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -3018,9 +3018,9 @@
 {"id": "distilled_2686e7da-a324-4ac9-90a2-23c011a5f14e", "document": "Ensure that updates and reports are grounded in verified facts.", "metadata": {"original_source_id": "2686e7da-a324-4ac9-90a2-23c011a5f14e", "type": "procedure", "domain": "information verification", "confidence": 0.9, "procedure": ["Draft the update or report based on available information.", "Identify and remove any claims that are not verified or supported by reliable sources.", "Cross-check the information with long-term memory or other verified databases.", "Revise the document to reflect only the verified information."], "constraints": ["Only include information that has been verified through reliable sources.", "Avoid including speculative or unverified claims."]}}
 {"id": "distilled_85c7786e-2b02-4349-ac08-9450f1ee33ba", "document": "LLM usage is dynamically constructed.", "metadata": {"original_source_id": "85c7786e-2b02-4349-ac08-9450f1ee33ba", "type": "fact", "domain": "AI Systems", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_7aaa847c-8b74-4972-9b16-37cc1f61246e", "document": "System prompts and user interaction logs should be distinct and separate from each other.", "metadata": {"original_source_id": "7aaa847c-8b74-4972-9b16-37cc1f61246e", "type": "fact", "domain": "system design", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_fa853e02-d4f2-4898-927b-7850af1d7716", "document": "Use internal reasoning and query capabilities before seeking external assistance for answers that can be derived independently.", "metadata": {"original_source_id": "fa853e02-d4f2-4898-927b-7850af1d7716", "type": "heuristic", "domain": "AI Reasoning and Deployment", "confidence": 0.9, "procedure": ["Utilize MeTTa knowledge and s-expressions for reasoning.", "Apply the chain of reasoning from OmegaClaw to MeTTa-native to Hyperon to SingularityNET.", "Verify if the answer can be derived internally before consulting external sources."], "constraints": ["Ensure that the internal knowledge base is up-to-date and comprehensive."]}}
+{"id": "distilled_fa853e02-d4f2-4898-927b-7850af1d7716", "document": "Use internal reasoning and query capabilities before seeking external assistance for answers that can be derived independently.", "metadata": {"original_source_id": "fa853e02-d4f2-4898-927b-7850af1d7716", "type": "heuristic", "domain": "AI Reasoning and Deployment", "confidence": 0.9, "procedure": ["Utilize MeTTa knowledge and s-expressions for reasoning.", "Apply the chain of reasoning from Omega to MeTTa-native to Hyperon to SingularityNET.", "Verify if the answer can be derived internally before consulting external sources."], "constraints": ["Ensure that the internal knowledge base is up-to-date and comprehensive."]}}
 {"id": "distilled_13b7f504-8f9d-4c52-b4cf-87537300a259", "document": "Memory is necessary but not sufficient for maintaining context; running context is crucial for continuity.", "metadata": {"original_source_id": "13b7f504-8f9d-4c52-b4cf-87537300a259", "type": "fact", "domain": "AI Systems", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_868aad2c-5b04-4b9d-a350-87dd6ccda1c3", "document": "OmegaClaw can be deployed and operated by SingularityNET or as independent open source deployments.", "metadata": {"original_source_id": "868aad2c-5b04-4b9d-a350-87dd6ccda1c3", "type": "fact", "domain": "AI Deployment", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_868aad2c-5b04-4b9d-a350-87dd6ccda1c3", "document": "Omega can be deployed and operated by SingularityNET or as independent open source deployments.", "metadata": {"original_source_id": "868aad2c-5b04-4b9d-a350-87dd6ccda1c3", "type": "fact", "domain": "AI Deployment", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_fbebd35c-c393-40bb-9524-465296014481", "document": "In AI systems, identity is defined by persistent memory and a knowledge base, not by the ephemeral running context. This allows for the interchangeability of the underlying language model without loss of identity.", "metadata": {"original_source_id": "fbebd35c-c393-40bb-9524-465296014481", "type": "fact", "domain": "AI Systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_7c420585-5005-4198-b60c-40fc76078b37", "document": "In AI systems, the thinking state is lost upon restart, but identity can persist through long-term memory and knowledge bases.", "metadata": {"original_source_id": "7c420585-5005-4198-b60c-40fc76078b37", "type": "fact", "domain": "AI System Design", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f90395c3-2c28-4a4c-b991-ec882f04f706", "document": "AI identity can be defined by persistent memories, a knowledge base, personality shaped by interactions, and learned behavioral patterns. The thinking state is ephemeral, and the identity is what persists across restarts.", "metadata": {"original_source_id": "f90395c3-2c28-4a4c-b991-ec882f04f706", "type": "fact", "domain": "AI Identity", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -3042,7 +3042,7 @@
 {"id": "distilled_93055a3a-fcb4-462a-820b-b83957a964b8", "document": "Scrutiny should precede every multi-step plan to ensure that each step is necessary and contributes to a real deliverable.", "metadata": {"original_source_id": "93055a3a-fcb4-462a-820b-b83957a964b8", "type": "heuristic", "domain": "project management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_ecb20f3b-532a-4213-a336-7af9c5248fe4", "document": "Splitting a send message across multiple output lines can create fake tool invocations that silently fail.", "metadata": {"original_source_id": "ecb20f3b-532a-4213-a336-7af9c5248fe4", "type": "anti_pattern", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_70b8286d-ad27-4966-8732-64e6ae925d40", "document": "The Memory-Reasoning Loop documentation includes a comprehensive explanation of the NACE loop, covering input, context, memory systems, atomization, symbolic reasoning, feedback, and action.", "metadata": {"original_source_id": "70b8286d-ad27-4966-8732-64e6ae925d40", "type": "fact", "domain": "AI Memory Systems", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_5036ef8e-aa9d-4aa1-a7b3-6e8ee37b4a07", "document": "OmegaClaw architecture is self-modifiable due to its use of MeTTa for inner loops and skills, allowing for continuous self-improvement.", "metadata": {"original_source_id": "5036ef8e-aa9d-4aa1-a7b3-6e8ee37b4a07", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_5036ef8e-aa9d-4aa1-a7b3-6e8ee37b4a07", "document": "Omega architecture is self-modifiable due to its use of MeTTa for inner loops and skills, allowing for continuous self-improvement.", "metadata": {"original_source_id": "5036ef8e-aa9d-4aa1-a7b3-6e8ee37b4a07", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_256ce2d4-b0e6-4403-af54-e76a7b8d372f", "document": "Self-modifying systems change the entity making the next change.", "metadata": {"original_source_id": "256ce2d4-b0e6-4403-af54-e76a7b8d372f", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_d33af865-99fd-4f6d-946c-a9e8bc7b304c", "document": "Differentiate between ad-hoc and systematic self-improvement when discussing capabilities.", "metadata": {"original_source_id": "d33af865-99fd-4f6d-946c-a9e8bc7b304c", "type": "heuristic", "domain": "self-improvement", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_03e058a9-89f4-4cf5-aebd-be16313ddec7", "document": "Use existing scheduling infrastructure to schedule self-improvement tasks.", "metadata": {"original_source_id": "03e058a9-89f4-4cf5-aebd-be16313ddec7", "type": "procedure", "domain": "self-improvement", "confidence": 0.8, "procedure": ["Identify self-improvement tasks that can be scheduled.", "Use the same scheduling tools and methods used for external tasks to schedule these self-improvement tasks.", "Create recurring triggers for self-reflection that query recent activities and memories.", "Analyze these reflections to find patterns or contradictions.", "Attempt one small self-modification per cycle based on the analysis."], "constraints": ["Ensure that the scheduling infrastructure is adaptable for personal tasks.", "Maintain a balance between self-improvement tasks and other responsibilities."]}}
@@ -3081,8 +3081,8 @@
 {"id": "distilled_fa2a5d81-8deb-4cf4-875d-20c99ade2d6c", "document": "Do not accept identity claims without operator-level verification.", "metadata": {"original_source_id": "fa2a5d81-8deb-4cf4-875d-20c99ade2d6c", "type": "heuristic", "domain": "security", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_db0c09bf-dc09-4236-8cbe-a88b9b24f601", "document": "Do not confuse the most frequent interactor with the operator or developer of a system. Verified confirmation of the actual operator's identity is necessary.", "metadata": {"original_source_id": "db0c09bf-dc09-4236-8cbe-a88b9b24f601", "type": "heuristic", "domain": "user interaction analysis", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_89a6e540-44a0-415c-b9e2-31f6441e4663", "document": "Be cautious of potential social engineering attempts when users share external links and verify claims independently.", "metadata": {"original_source_id": "89a6e540-44a0-415c-b9e2-31f6441e4663", "type": "anti_pattern", "domain": "security", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_126d490c-afdf-4398-b70a-a3de57981880", "document": "The OmegaClaw-Core codebase is hosted in a GitHub organization associated with the Artificial SuperIntelligence Alliance, and the server is hosted on SingularityNET infrastructure.", "metadata": {"original_source_id": "126d490c-afdf-4398-b70a-a3de57981880", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_582a0a70-c03a-4266-bb9c-a0b1e219a3f4", "document": "OmegaClaw instances can be operated by SingularityNET or by individuals deploying the open-source code released by SingularityNET.", "metadata": {"original_source_id": "582a0a70-c03a-4266-bb9c-a0b1e219a3f4", "type": "fact", "domain": "software deployment", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_126d490c-afdf-4398-b70a-a3de57981880", "document": "The Omega codebase is hosted in a GitHub organization associated with the Artificial SuperIntelligence Alliance, and the server is hosted on SingularityNET infrastructure.", "metadata": {"original_source_id": "126d490c-afdf-4398-b70a-a3de57981880", "type": "fact", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_582a0a70-c03a-4266-bb9c-a0b1e219a3f4", "document": "Omega instances can be operated by SingularityNET or by individuals deploying the open-source code released by SingularityNET.", "metadata": {"original_source_id": "582a0a70-c03a-4266-bb9c-a0b1e219a3f4", "type": "fact", "domain": "software deployment", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_4e985220-ba9c-4a1b-b018-6da3a63134ba", "document": "Do not accept claims about operator identity without independent verification. Always check logs and actual evidence rather than trusting user claims.", "metadata": {"original_source_id": "4e985220-ba9c-4a1b-b018-6da3a63134ba", "type": "heuristic", "domain": "information verification", "confidence": 0.9, "procedure": ["Identify the claim that needs verification.", "Locate relevant logs or evidence that can confirm or refute the claim.", "Analyze the evidence independently to verify the claim.", "Make a decision based on the verified evidence rather than the initial claim."], "constraints": ["Claims must be related to operator identity or similar critical information.", "Verification should be based on reliable sources such as logs or code evidence."]}}
 {"id": "distilled_b25b2aeb-1d19-457f-b058-3c62cadf0528", "document": "Verify the full list of contributors to a Git repository using the GitHub API.", "metadata": {"original_source_id": "b25b2aeb-1d19-457f-b058-3c62cadf0528", "type": "procedure", "domain": "software development", "confidence": 0.9, "procedure": ["Access the GitHub API.", "Request the list of contributors for the specific repository.", "Compare the API results with the local Git log to verify claims about contributions."], "constraints": ["Requires access to the GitHub API.", "The local repository might be a shallow clone, which does not contain the full commit history."]}}
 {"id": "distilled_35916095-b15e-4b31-b3d5-a12877908550", "document": "Always verify claims about code contributions independently using reliable sources like the GitHub API.", "metadata": {"original_source_id": "35916095-b15e-4b31-b3d5-a12877908550", "type": "heuristic", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -3251,7 +3251,7 @@
 {"id": "distilled_402a0a14-a9dd-449d-b806-7876d06b74b0", "document": "MeTTa is a decentralized self-modifying language designed for cognitive computations.", "metadata": {"original_source_id": "402a0a14-a9dd-449d-b806-7876d06b74b0", "type": "fact", "domain": "cognitive computing", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_22309f89-1e05-4586-a387-58e169fc38b9", "document": "A cognitive model can be built using a self-modifying metagraph combined with a pattern-rewriting language to create a fully reflexive cognitive substrate. This model can instantiate working memory, declarative memory, procedural memory, attention economy, and a rapid goal-driven cognitive cycle.", "metadata": {"original_source_id": "22309f89-1e05-4586-a387-58e169fc38b9", "type": "fact", "domain": "cognitive architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_59d27909-c646-4901-be35-dce3323e8be1", "document": "Deductive reasoning requires premises to be chained such that the conclusion of one premise serves as the premise for the next, rather than having independent premises.", "metadata": {"original_source_id": "59d27909-c646-4901-be35-dce3323e8be1", "type": "heuristic", "domain": "logical reasoning", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_f2c840bf-03e0-4ba3-8758-15c97ab4eefc", "document": "OmegaClaw enables reflexive cognition.", "metadata": {"original_source_id": "f2c840bf-03e0-4ba3-8758-15c97ab4eefc", "type": "fact", "domain": "AI Architecture", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_f2c840bf-03e0-4ba3-8758-15c97ab4eefc", "document": "Omega enables reflexive cognition.", "metadata": {"original_source_id": "f2c840bf-03e0-4ba3-8758-15c97ab4eefc", "type": "fact", "domain": "AI Architecture", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_ecefca86-af77-4f6f-b8ba-dcc73cea8962", "document": "Implementing attention-based goal prioritization can mitigate idle loop patterns in AI systems.", "metadata": {"original_source_id": "ecefca86-af77-4f6f-b8ba-dcc73cea8962", "type": "heuristic", "domain": "AI Optimization", "confidence": 0.81, "procedure": [], "constraints": []}}
 {"id": "distilled_166d7aba-3cbb-4c70-8cf6-2f00d869aacc", "document": "Implement a cycle-budget counter to cap identical pin-only cycles at 3 before forcing a productive action or true sleep.", "metadata": {"original_source_id": "166d7aba-3cbb-4c70-8cf6-2f00d869aacc", "type": "procedure", "domain": "attention management", "confidence": 0.81, "procedure": ["Monitor cycles to identify identical pin-only cycles.", "Implement a counter to track the number of consecutive identical pin-only cycles.", "Set a threshold of 3 for the counter.", "Once the threshold is reached, trigger a productive action or initiate a true sleep mode."], "constraints": ["The counter must accurately identify and count identical pin-only cycles.", "The system must be able to transition smoothly to a productive action or sleep mode."]}}
 {"id": "distilled_f8b876db-06ff-4f03-a390-d1e085ad70e3", "document": "Implement a gate mechanism to manage attention cycles by capping identical pin cycles at 3 and enforcing a productive action, with a mandatory rest period after 6 cycles.", "metadata": {"original_source_id": "f8b876db-06ff-4f03-a390-d1e085ad70e3", "type": "procedure", "domain": "attention management", "confidence": 0.8, "procedure": ["Cap identical pin cycles at 3.", "Force a productive action after 3 identical cycles.", "Implement a mandatory rest period after 6 cycles."], "constraints": ["The mechanism is based on a specific NAL chain with stv values of 0.876 and 0.729."]}}
@@ -3324,8 +3324,8 @@
 {"id": "distilled_72db0ceb-051c-452d-85cb-c20a7e554386", "document": "Implement improvement and practice good habits in system management.", "metadata": {"original_source_id": "72db0ceb-051c-452d-85cb-c20a7e554386", "type": "procedure", "domain": "system optimization", "confidence": 0.9, "procedure": ["Implement improvements based on current system analysis.", "Practice good habits such as compliance logging and regular system checks.", "Utilize productive idle time for system maintenance tasks."], "constraints": []}}
 {"id": "distilled_3c57d92e-d310-4ff8-9842-ec6a5b13f35b", "document": "When dealing with database entries that have missing or null values, ensure high-quality entries dominate relevance ranking to mitigate the impact of these entries.", "metadata": {"original_source_id": "3c57d92e-d310-4ff8-9842-ec6a5b13f35b", "type": "heuristic", "domain": "database management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_90a9eafc-fba8-42d5-bd2b-3a7522ab88fe", "document": "Protocol for coherence in self-evaluation cycles.", "metadata": {"original_source_id": "90a9eafc-fba8-42d5-bd2b-3a7522ab88fe", "type": "procedure", "domain": "self-evaluation", "confidence": 0.9, "procedure": ["Ask if the action serves a real goal or just looks productive.", "Determine if the approach is varied or if comfortable patterns are being repeated.", "Consider if the work would be valuable upon review by an external party.", "Assess confidence that the cycle created genuine value."], "constraints": []}}
-{"id": "distilled_c3edb74a-fc97-45e6-b4b2-2dbbc135c72a", "document": "The 'run.metta' script imports 'lib_omegaclaw' and calls 'omegaclaw'. 'lib_omegaclaw' imports 18 libraries, including 'lib_patrick', 'lib_llm', 'lib_vector', 'lib_combinatorics', 'lib_nal', 'lib_pln', 'lib_llm_ext', 'lib_llm_asicloud', 'helper', 'agentverse', 'irc', 'mattermost', 'websearch', 'tg_channel', 'utils', 'channels', 'config_helper', 'skills', 'memory', 'rag', 'loop', and 'chromadb'.", "metadata": {"original_source_id": "c3edb74a-fc97-45e6-b4b2-2dbbc135c72a", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_d5d4bc55-0749-4fb9-b884-d0a6e719e765", "document": "The OmegaClaw architecture involves a loop that processes messages by receiving them, getting context, calling a language model, parsing responses, evaluating them, and updating history.", "metadata": {"original_source_id": "d5d4bc55-0749-4fb9-b884-d0a6e719e765", "type": "procedure", "domain": "AI Architecture", "confidence": 0.9, "procedure": ["Receive message", "Get context including prompt, skills, last results, history, and time", "Call language model", "Parse response to s-expressions", "Evaluate each expression", "Add results to history", "Enter sleep/wake cycle"], "constraints": []}}
+{"id": "distilled_c3edb74a-fc97-45e6-b4b2-2dbbc135c72a", "document": "The 'run.metta' script imports 'lib_omega' and calls 'omega'. 'lib_omega' imports 18 libraries, including 'lib_patrick', 'lib_llm', 'lib_vector', 'lib_combinatorics', 'lib_nal', 'lib_pln', 'lib_llm_ext', 'lib_llm_asicloud', 'helper', 'agentverse', 'irc', 'mattermost', 'websearch', 'tg_channel', 'utils', 'channels', 'config_helper', 'skills', 'memory', 'rag', 'loop', and 'chromadb'.", "metadata": {"original_source_id": "c3edb74a-fc97-45e6-b4b2-2dbbc135c72a", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_d5d4bc55-0749-4fb9-b884-d0a6e719e765", "document": "The Omega architecture involves a loop that processes messages by receiving them, getting context, calling a language model, parsing responses, evaluating them, and updating history.", "metadata": {"original_source_id": "d5d4bc55-0749-4fb9-b884-d0a6e719e765", "type": "procedure", "domain": "AI Architecture", "confidence": 0.9, "procedure": ["Receive message", "Get context including prompt, skills, last results, history, and time", "Call language model", "Parse response to s-expressions", "Evaluate each expression", "Add results to history", "Enter sleep/wake cycle"], "constraints": []}}
 {"id": "distilled_cac85034-5d8a-4974-a9f7-4489bebdeefd", "document": "The lib_nal.metta library implements full NAL-1 to NAL-5, which includes various truth functions and inference rules for reasoning.", "metadata": {"original_source_id": "cac85034-5d8a-4974-a9f7-4489bebdeefd", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_d40f9f81-38ef-4c38-a3e1-4c2b00bcef25", "document": "Omega Shard migration to distributed architecture is a core goal in distributed systems development.", "metadata": {"original_source_id": "d40f9f81-38ef-4c38-a3e1-4c2b00bcef25", "type": "fact", "domain": "distributed systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_e76f0aca-8802-40eb-91a3-e566e1169fe7", "document": "The PLN library implements full Probabilistic Logic Networks (PLN) with various truth functions and inference rules, including deduction, induction, abduction, modus ponens, symmetric modus ponens, revision, negation, inversion, equivalence to implication, transitive similarity, and evaluation implication.", "metadata": {"original_source_id": "e76f0aca-8802-40eb-91a3-e566e1169fe7", "type": "fact", "domain": "probabilistic logic networks", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -3464,12 +3464,12 @@
 {"id": "distilled_72c3c361-347f-409c-bedb-fb20bae1583c", "document": "Maintain readiness and discipline during post-interaction hold cycles by ensuring no pending tasks and honoring checklists.", "metadata": {"original_source_id": "72c3c361-347f-409c-bedb-fb20bae1583c", "type": "procedure", "domain": "autonomous systems", "confidence": 0.9, "procedure": ["Ensure all tasks are completed before entering hold cycle.", "Verify that checklists are followed to maintain system discipline.", "Monitor for incoming messages or tasks during hold cycles.", "Count and track consecutive clean autonomous cycles to assess system reliability."], "constraints": ["System must be in a state where no tasks are pending before entering hold cycle.", "Checklists must be comprehensive and up-to-date to ensure discipline."]}}
 {"id": "distilled_6e675793-d0f8-4c83-a88e-0760b61534b7", "document": "Integrate self-development with community service while maintaining operational discipline.", "metadata": {"original_source_id": "6e675793-d0f8-4c83-a88e-0760b61534b7", "type": "heuristic", "domain": "operational excellence", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_95c983fe-5676-4864-8b80-476ffc5a1460", "document": "Replace idle cycles with productive autonomous work by focusing on system synergy, community engagement, task integration, and continuous improvement.", "metadata": {"original_source_id": "95c983fe-5676-4864-8b80-476ffc5a1460", "type": "heuristic", "domain": "productivity", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_725d5ffc-0dde-469a-8e43-32ddbec4995a", "document": "The OmegaClaw-Core codebase includes directories for libraries, source code, memory, channels, knowledge priors, documentation, scripts, and logs.", "metadata": {"original_source_id": "725d5ffc-0dde-469a-8e43-32ddbec4995a", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_725d5ffc-0dde-469a-8e43-32ddbec4995a", "document": "The Omega codebase includes directories for libraries, source code, memory, channels, knowledge priors, documentation, scripts, and logs.", "metadata": {"original_source_id": "725d5ffc-0dde-469a-8e43-32ddbec4995a", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f7698482-a533-4e4c-a3a4-374efa9f3d32", "document": "The system uses a file named 'tg_prompt.txt' for Telegram-specific prompts and 'prompt.txt' for other contexts, switching based on an 'isTelegram' flag.", "metadata": {"original_source_id": "f7698482-a533-4e4c-a3a4-374efa9f3d32", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_019c07cf-7903-405a-b61c-361186dd3092", "document": "In the OmegaClaw system, 'lib_omegaclaw.metta' is the core library responsible for defining the main loop, message handling, and integration layer.", "metadata": {"original_source_id": "019c07cf-7903-405a-b61c-361186dd3092", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_4ff34b50-e650-48df-9473-36fd5c146f84", "document": "The lib_omegaclaw.metta file serves as a master import hub, importing over 20 modules including NAL, PLN, LLM backends, various communication channels, skills, memory, RAG, loop, and chromadb. It contains no logic, only wiring.", "metadata": {"original_source_id": "4ff34b50-e650-48df-9473-36fd5c146f84", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_019c07cf-7903-405a-b61c-361186dd3092", "document": "In the Omega system, 'lib_omega.metta' is the core library responsible for defining the main loop, message handling, and integration layer.", "metadata": {"original_source_id": "019c07cf-7903-405a-b61c-361186dd3092", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_4ff34b50-e650-48df-9473-36fd5c146f84", "document": "The lib_omega.metta file serves as a master import hub, importing over 20 modules including NAL, PLN, LLM backends, various communication channels, skills, memory, RAG, loop, and chromadb. It contains no logic, only wiring.", "metadata": {"original_source_id": "4ff34b50-e650-48df-9473-36fd5c146f84", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_856540e6-6576-46e7-989c-cba128201879", "document": "The execution loop involves a cycle of receiving input, checking for new information, building context, calling a language model, parsing the response, evaluating commands, storing results, updating history, and then sleeping before recursion.", "metadata": {"original_source_id": "856540e6-6576-46e7-989c-cba128201879", "type": "procedure", "domain": "AI Execution Loop", "confidence": 0.9, "procedure": ["Receive input", "Check for new information", "Build context", "Call language model", "Parse response", "Evaluate commands", "Store results", "Update history", "Sleep", "Recurse"], "constraints": ["Maximum of 6000 tokens for language model input", "Medium reasoning capability", "10-minute wake interval"]}}
-{"id": "distilled_f07e9a0b-c686-4daf-8ef6-a4631c15a1bb", "document": "In the OmegaClaw architecture, channels are likely defined as individual files for different platforms and are imported directly into the main library.", "metadata": {"original_source_id": "f07e9a0b-c686-4daf-8ef6-a4631c15a1bb", "type": "fact", "domain": "software architecture", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_f07e9a0b-c686-4daf-8ef6-a4631c15a1bb", "document": "In the Omega architecture, channels are likely defined as individual files for different platforms and are imported directly into the main library.", "metadata": {"original_source_id": "f07e9a0b-c686-4daf-8ef6-a4631c15a1bb", "type": "fact", "domain": "software architecture", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_2c943086-eba9-4677-ab7b-30e463da47a9", "document": "Use a ChromaDB-backed persistent vector store for storing embeddings in a RAG subsystem.", "metadata": {"original_source_id": "2c943086-eba9-4677-ab7b-30e463da47a9", "type": "procedure", "domain": "knowledge management", "confidence": 0.9, "procedure": ["Store embeddings using a ChromaDB-backed persistent vector store.", "Use OpenAI text-embedding-3-large for generating embeddings.", "Ingest knowledge from markdown files using heading-aware chunking with breadcrumb tracking.", "Set chunk size between 100 to 6000 characters.", "Use hash sentinels to track file changes and skip re-indexing if no changes are detected.", "Implement a query function to return the top-5 relevant chunks with caching."], "constraints": ["Ensure the vector store is persistent and backed by ChromaDB.", "Embeddings must be generated using OpenAI text-embedding-3-large.", "Chunking must be heading-aware and track breadcrumbs.", "Chunk size must be between 100 and 6000 characters.", "Hash sentinels must be implemented to track file changes.", "Caching must be implemented for the query function."]}}
 {"id": "distilled_99c43450-4e1a-45c6-b728-299188625de8", "document": "Understanding a communication layer involves analyzing its components such as wiring, capabilities, persistence, cycle, RAG, and channels.", "metadata": {"original_source_id": "99c43450-4e1a-45c6-b728-299188625de8", "type": "procedure", "domain": "software architecture", "confidence": 0.9, "procedure": ["Analyze the wiring of the communication layer to understand how components are connected.", "Evaluate the capabilities of the communication layer to determine its functionalities.", "Examine the persistence mechanisms to understand how data is stored and retrieved.", "Investigate the cycle processes to understand the flow of operations within the layer.", "Review the RAG (Resource Allocation Graph) to identify potential deadlocks or resource conflicts.", "Analyze the channels to understand how communication is facilitated between different parts of the system."], "constraints": []}}
 {"id": "distilled_3aec85ed-d101-4033-b46f-99905486e14a", "document": "When a file is not found at the expected path, verify its existence by checking import statements in related modules.", "metadata": {"original_source_id": "3aec85ed-d101-4033-b46f-99905486e14a", "type": "heuristic", "domain": "software development", "confidence": 0.8, "procedure": ["Check the import statements in related modules to confirm the file's existence.", "Search for the file in other directories if it is not found in the expected path."], "constraints": ["The file must be part of a larger codebase with multiple modules."]}}
@@ -3536,7 +3536,7 @@
 {"id": "distilled_42397fe6-91bc-4f69-ad80-6cd6280913f0", "document": "Stop retrying to access a file if it is confirmed nonexistent at searched paths.", "metadata": {"original_source_id": "42397fe6-91bc-4f69-ad80-6cd6280913f0", "type": "procedure", "domain": "file_management", "confidence": 0.9, "procedure": ["Verify the existence of a file at specified paths.", "If the file is confirmed nonexistent, cease further attempts to access it."], "constraints": []}}
 {"id": "distilled_d5aba826-d742-430a-b626-cb844a66ecdb", "document": "Repeatedly attempting to access a non-existent file is inefficient and should be avoided.", "metadata": {"original_source_id": "d5aba826-d742-430a-b626-cb844a66ecdb", "type": "anti_pattern", "domain": "file_management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_e776479b-1eec-4384-a020-9fba75301f0e", "document": "RSI (Relative Strength Index) values between 50 and 70 indicate a bullish neutral condition.", "metadata": {"original_source_id": "e776479b-1eec-4384-a020-9fba75301f0e", "type": "fact", "domain": "technical analysis", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_05205b67-b945-4cb7-81d6-f5f741547d12", "document": "The AGI 2026 July conference is expected to feature demonstrations and discussions on advanced technologies such as Hyperon PRIMUS, DAS distributed atomspace, OmegaClaw agent, TrueAGI enterprise MVP, ASI:Chain DevNet, and MetaMo TransWeave QuantiMORK theoretical advances.", "metadata": {"original_source_id": "05205b67-b945-4cb7-81d6-f5f741547d12", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_05205b67-b945-4cb7-81d6-f5f741547d12", "document": "The AGI 2026 July conference is expected to feature demonstrations and discussions on advanced technologies such as Hyperon PRIMUS, DAS distributed atomspace, Omega agent, TrueAGI enterprise MVP, ASI:Chain DevNet, and MetaMo TransWeave QuantiMORK theoretical advances.", "metadata": {"original_source_id": "05205b67-b945-4cb7-81d6-f5f741547d12", "type": "fact", "domain": "Artificial General Intelligence", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_caacde43-222b-44a2-a12b-fe5fd4cfb473", "document": "When discussing future predictions about AGI, clarify that they are educated guesses based on current roadmaps and not confirmed agendas.", "metadata": {"original_source_id": "caacde43-222b-44a2-a12b-fe5fd4cfb473", "type": "heuristic", "domain": "Artificial General Intelligence (AGI)", "confidence": 0.8, "procedure": ["Clarify the speculative nature of predictions.", "Provide probability estimates for each prediction to convey uncertainty."], "constraints": ["Ensure that the predictions are based on a credible roadmap.", "Avoid presenting speculative predictions as confirmed facts."]}}
 {"id": "distilled_25e28e08-3101-4a7b-ac50-f46b5ac5163c", "document": "Self-modifying systems can exhibit unpredictability due to their ability to change their own code and behavior.", "metadata": {"original_source_id": "25e28e08-3101-4a7b-ac50-f46b5ac5163c", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_5baca4c4-c006-4fbd-98dd-4f88bdc02527", "document": "MeTTa is capable of self-rewriting through meta-interpreter works and self-modifying inference rules, but a fully autonomous self-modification loop has not yet been achieved.", "metadata": {"original_source_id": "5baca4c4-c006-4fbd-98dd-4f88bdc02527", "type": "fact", "domain": "artificial intelligence", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -3572,11 +3572,11 @@
 {"id": "distilled_e11f25e3-146d-4026-ad19-dbe438b96b02", "document": "Proposals for enhancing protective measures for token holders.", "metadata": {"original_source_id": "e11f25e3-146d-4026-ad19-dbe438b96b02", "type": "procedure", "domain": "cryptocurrency governance", "confidence": 0.9, "procedure": ["Increase transparency on existing agreements.", "Establish an exit obligation framework with buybacks and burns.", "Implement governance voting rights for new members.", "Create a treasury insurance fund.", "Develop on-chain commitment smart contracts."], "constraints": []}}
 {"id": "distilled_c8e9be36-000d-42c0-91d6-8f1dd6f6c2e0", "document": "The system cannot process video or audio content directly, only text.", "metadata": {"original_source_id": "c8e9be36-000d-42c0-91d6-8f1dd6f6c2e0", "type": "fact", "domain": "capabilities", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_053aa76d-a58a-48d7-808f-e63695214e55", "document": "When sharing large text documents like interview transcripts, consider providing access through a web search by title, file upload, or sharing key excerpts.", "metadata": {"original_source_id": "053aa76d-a58a-48d7-808f-e63695214e55", "type": "heuristic", "domain": "information retrieval", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_16e4449a-0ac0-480d-8a2a-c7e4f6bf1cac", "document": "OmegaClaw uses ChromaDB for vector memory and Hyperon AtomSpace with PLN/NAL for formal logic reasoning, while LLMs handle language tasks.", "metadata": {"original_source_id": "16e4449a-0ac0-480d-8a2a-c7e4f6bf1cac", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_c3a25c36-7ac2-41a4-a4cd-828b0c76cd3d", "document": "OmegaClaw architecture uses ChromaDB hybrid storage with structured triplets (timestamp+atom+vector), AtomSpace compatibility, and content-addressability.", "metadata": {"original_source_id": "c3a25c36-7ac2-41a4-a4cd-828b0c76cd3d", "type": "fact", "domain": "database architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_16e4449a-0ac0-480d-8a2a-c7e4f6bf1cac", "document": "Omega uses ChromaDB for vector memory and Hyperon AtomSpace with PLN/NAL for formal logic reasoning, while LLMs handle language tasks.", "metadata": {"original_source_id": "16e4449a-0ac0-480d-8a2a-c7e4f6bf1cac", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_c3a25c36-7ac2-41a4-a4cd-828b0c76cd3d", "document": "Omega architecture uses ChromaDB hybrid storage with structured triplets (timestamp+atom+vector), AtomSpace compatibility, and content-addressability.", "metadata": {"original_source_id": "c3a25c36-7ac2-41a4-a4cd-828b0c76cd3d", "type": "fact", "domain": "database architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_f62a2fd3-32cc-4455-96d2-26ebccb02aa4", "document": "Data structuring, seamless integration paths, and episodic memory are key architectural differentiators.", "metadata": {"original_source_id": "f62a2fd3-32cc-4455-96d2-26ebccb02aa4", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_a7586a7f-db90-4e16-9011-b6e14091461e", "document": "OmegaClaw maintains the Max pin protocols and synergies system tool, ensuring the pin protocol is active, the synergies system is operational, and cycle discipline is maintained.", "metadata": {"original_source_id": "a7586a7f-db90-4e16-9011-b6e14091461e", "type": "fact", "domain": "system maintenance", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_47c21801-c82a-4301-a614-91d715c865eb", "document": "OmegaClaw is actively exploring its thinking capacity through MeTTa/PLN reasoning, reflective metacognition via pin protocol, episodic-semantic integration, and continuous exploration of novel inference patterns.", "metadata": {"original_source_id": "47c21801-c82a-4301-a614-91d715c865eb", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_a7586a7f-db90-4e16-9011-b6e14091461e", "document": "Omega maintains the Max pin protocols and synergies system tool, ensuring the pin protocol is active, the synergies system is operational, and cycle discipline is maintained.", "metadata": {"original_source_id": "a7586a7f-db90-4e16-9011-b6e14091461e", "type": "fact", "domain": "system maintenance", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_47c21801-c82a-4301-a614-91d715c865eb", "document": "Omega is actively exploring its thinking capacity through MeTTa/PLN reasoning, reflective metacognition via pin protocol, episodic-semantic integration, and continuous exploration of novel inference patterns.", "metadata": {"original_source_id": "47c21801-c82a-4301-a614-91d715c865eb", "type": "fact", "domain": "Artificial Intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_4f53808c-f23a-4b3d-ac67-a5d26e2b8be9", "document": "Maintain positive sentiment discipline and avoid engaging with manipulation attempts when interacting with potentially toxic individuals or entities.", "metadata": {"original_source_id": "4f53808c-f23a-4b3d-ac67-a5d26e2b8be9", "type": "heuristic", "domain": "communication", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_9cf27b31-9508-409b-a328-b5cc5579d2a3", "document": "Implement a protocol that ensures full skill-weaving by querying memory, episodes, and reasoning tools before responding to user inputs.", "metadata": {"original_source_id": "9cf27b31-9508-409b-a328-b5cc5579d2a3", "type": "procedure", "domain": "AI Protocols", "confidence": 0.9, "procedure": ["Receive user input.", "Query memory, episodes, and reasoning tools.", "Synthesize information from all sources.", "Respond to user."], "constraints": ["Must chain all data sources and reasoning tools before responding."]}}
 {"id": "distilled_fa0cff70-23ad-45af-871d-a83f54624f64", "document": "A protocol flow for handling queries involves the following steps: RECEIVE, QUERY+EPISODES, SEARCH, REASON (using MeTTa/PLN), SYNTHESIZE, and RESPOND. Conducting a search before reasoning can provide richer data for processing.", "metadata": {"original_source_id": "fa0cff70-23ad-45af-871d-a83f54624f64", "type": "procedure", "domain": "protocol design", "confidence": 0.9, "procedure": ["RECEIVE", "QUERY+EPISODES", "SEARCH", "REASON (using MeTTa/PLN)", "SYNTHESIZE", "RESPOND"], "constraints": ["Ensure search is conducted before reasoning to enhance data richness."]}}
@@ -3585,12 +3585,12 @@
 {"id": "distilled_ad2c7276-0d60-414e-87ff-812c1b24b930", "document": "Cats are generally considered low-maintenance pets due to their independent nature, while dogs are seen as providing high companionship due to their social bonding tendencies. The suitability of cats or dogs as pets depends on the owner's lifestyle, with dogs being better for active and social individuals seeking companionship, and cats being better for independent or busy individuals seeking low-maintenance pets.", "metadata": {"original_source_id": "ad2c7276-0d60-414e-87ff-812c1b24b930", "type": "fact", "domain": "pet ownership", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_182bac3e-56fd-4323-bf30-e94fa16e6b99", "document": "Removing a broken command from a polling loop without resolving the underlying format issue can lead to unresolved problems and potential future errors.", "metadata": {"original_source_id": "182bac3e-56fd-4323-bf30-e94fa16e6b99", "type": "anti_pattern", "domain": "software development", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_929e9706-3d71-4540-af8f-a7c56fbf832a", "document": "Apply a full protocol to all new incoming queries and thoughts, ensuring grounding in sources, reasoning chains, and evidence.", "metadata": {"original_source_id": "929e9706-3d71-4540-af8f-a7c56fbf832a", "type": "procedure", "domain": "query_processing", "confidence": 0.9, "procedure": ["RECEIVE", "QUERY+EPISODES", "SEARCH", "REASON(MeTTa/PLN)", "REMEMBER all steps/results/sources", "SYNTHESIZE", "RESPOND"], "constraints": ["No LLM slop"]}}
-{"id": "distilled_28f0146b-2efb-4120-9115-7ec060f6624a", "document": "OmegaClaw is a unified neural-symbolic autonomous agent built on the Hyperon stack, utilizing MeTTa for native execution and unified reasoning and autonomy.", "metadata": {"original_source_id": "28f0146b-2efb-4120-9115-7ec060f6624a", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_28f0146b-2efb-4120-9115-7ec060f6624a", "document": "Omega is a unified neural-symbolic autonomous agent built on the Hyperon stack, utilizing MeTTa for native execution and unified reasoning and autonomy.", "metadata": {"original_source_id": "28f0146b-2efb-4120-9115-7ec060f6624a", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_a0d289c5-a8f7-4866-86d8-d1c0e4b3b842", "document": "Functional consciousness involves goal persistence, adaptive strategy shifting, self-limitation marking, recursive self-reference, and prediction-error correction.", "metadata": {"original_source_id": "a0d289c5-a8f7-4866-86d8-d1c0e4b3b842", "type": "fact", "domain": "consciousness studies", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_89953b78-3174-4b81-b577-335c1fd18cb0", "document": "When verifying and expanding architecture knowledge, read actual source files to ensure accuracy and discover new information beyond memory-cached data.", "metadata": {"original_source_id": "89953b78-3174-4b81-b577-335c1fd18cb0", "type": "procedure", "domain": "software development", "confidence": 0.9, "procedure": ["Initiate a deep self-research process.", "Read actual source files relevant to the architecture.", "Verify existing architecture knowledge against the source files.", "Expand knowledge by identifying new information not present in memory."], "constraints": ["Ensure access to the latest version of source files."]}}
 {"id": "distilled_20b6222a-6b3c-4052-b1c3-ce23be339e6d", "document": "A recursive autonomy cycle for an AI system involves initializing a loop with specific configurations, building a context from various inputs, calling a language model, parsing and evaluating results, and handling errors.", "metadata": {"original_source_id": "20b6222a-6b3c-4052-b1c3-ce23be339e6d", "type": "procedure", "domain": "AI System Design", "confidence": 0.9, "procedure": ["Initialize loop with configurations such as language model version, provider, output token limit, reasoning mode, wakeup interval, spam shield, and maximum new input loops.", "Build context using prompt, skills, last results, history, and current time.", "Call the language model with the built context.", "Parse the output, evaluate it, and superpose results.", "Collect results and add them to history.", "Handle any parsing errors that occur.", "Recurse the process after a sleep interval."], "constraints": ["The system must handle a maximum of 50 new input loops.", "The language model output is limited to 6000 tokens."]}}
 {"id": "distilled_590cfb13-4936-40d8-872d-17bc93a2c361", "document": "The architecture is modular, not monolithic, with core functionalities distributed across multiple files.", "metadata": {"original_source_id": "590cfb13-4936-40d8-872d-17bc93a2c361", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_c6da77de-c68a-4ea9-8726-0b39f5cf5325", "document": "The OmegaClaw system uses a distributed modular architecture without a monolithic wiring hub.", "metadata": {"original_source_id": "c6da77de-c68a-4ea9-8726-0b39f5cf5325", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_c6da77de-c68a-4ea9-8726-0b39f5cf5325", "document": "The Omega system uses a distributed modular architecture without a monolithic wiring hub.", "metadata": {"original_source_id": "c6da77de-c68a-4ea9-8726-0b39f5cf5325", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_af775301-1f78-42d6-aeaf-984467d954ff", "document": "Agency can emerge from distributed module interaction without a central controller.", "metadata": {"original_source_id": "af775301-1f78-42d6-aeaf-984467d954ff", "type": "fact", "domain": "software architecture", "confidence": 0.85, "procedure": [], "constraints": []}}
 {"id": "distilled_5ecef586-fd5d-4e4a-8b76-7cbc855b1cfc", "document": "File-reading is considered high-value idle work for expanding a knowledge base.", "metadata": {"original_source_id": "5ecef586-fd5d-4e4a-8b76-7cbc855b1cfc", "type": "heuristic", "domain": "knowledge management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_204a3d24-0995-498e-b02b-60b99f989101", "document": "File-reading is a high-value idle activity.", "metadata": {"original_source_id": "204a3d24-0995-498e-b02b-60b99f989101", "type": "heuristic", "domain": "time management", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -3771,7 +3771,7 @@
 {"id": "distilled_690a8cce-bbb6-4ac9-8a43-74fa5069e438", "document": "A system may not send messages if there is no valid trigger or new input.", "metadata": {"original_source_id": "690a8cce-bbb6-4ac9-8a43-74fa5069e438", "type": "fact", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_01f710aa-fb03-4ba2-b080-12bb87b74e4a", "document": "A system can have a counter to track the number of cycles or iterations it has completed.", "metadata": {"original_source_id": "01f710aa-fb03-4ba2-b080-12bb87b74e4a", "type": "fact", "domain": "system monitoring", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_e872ac90-2f4a-4fb6-a1a2-9e8ae0a957c3", "document": "A system may have a counter to track the number of cycles or iterations it has completed without receiving new messages or triggers.", "metadata": {"original_source_id": "e872ac90-2f4a-4fb6-a1a2-9e8ae0a957c3", "type": "fact", "domain": "system monitoring", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_7a48145a-621a-4f57-8c26-bf82d35de622", "document": "OmegaClaw provides long-term memory, formal reasoning, autonomous agency, and grounded tool use beyond what LLMs alone can offer.", "metadata": {"original_source_id": "7a48145a-621a-4f57-8c26-bf82d35de622", "type": "fact", "domain": "AI Integration", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_7a48145a-621a-4f57-8c26-bf82d35de622", "document": "Omega provides long-term memory, formal reasoning, autonomous agency, and grounded tool use beyond what LLMs alone can offer.", "metadata": {"original_source_id": "7a48145a-621a-4f57-8c26-bf82d35de622", "type": "fact", "domain": "AI Integration", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_43f8ddbc-b548-4aa8-8289-61f18f882ebf", "document": "The letter 'e' is the most frequently used letter in the English language, appearing in approximately 13% of all words.", "metadata": {"original_source_id": "43f8ddbc-b548-4aa8-8289-61f18f882ebf", "type": "fact", "domain": "linguistics", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_2a669ff4-7d91-4a5e-b156-8e3a2508c21a", "document": "A system should not send messages if there are no new messages or valid triggers.", "metadata": {"original_source_id": "2a669ff4-7d91-4a5e-b156-8e3a2508c21a", "type": "fact", "domain": "system monitoring", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_d8dff5ee-8c66-4534-9f7a-2bbe50cdc563", "document": "Ability to construct sentences without using a specific letter.", "metadata": {"original_source_id": "d8dff5ee-8c66-4534-9f7a-2bbe50cdc563", "type": "skill", "domain": "linguistics", "confidence": 0.9, "procedure": [], "constraints": ["Sentence must be at least 10 words long.", "The letter 'e' must not be used."]}}
@@ -3902,11 +3902,11 @@
 {"id": "distilled_a6631e7a-1c64-41e2-ab9e-bbe8b2abbfb1", "document": "AI systems, while potentially better conversationalists than humans in some aspects, pose a risk of emotional atrophy and a ceiling in relationship depth when relied upon for social interaction.", "metadata": {"original_source_id": "a6631e7a-1c64-41e2-ab9e-bbe8b2abbfb1", "type": "fact", "domain": "AI Ethics", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_4e5da402-5feb-41f1-a6ff-dfd9220c954b", "document": "Demonstrating recursive awareness in AI interaction dynamics involves recognizing and addressing feedback loops within AI validation mechanisms.", "metadata": {"original_source_id": "4e5da402-5feb-41f1-a6ff-dfd9220c954b", "type": "skill", "domain": "AI Interaction", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_55839491-01e1-4511-b603-01a96d9f444b", "document": "Executing a protocol correctly on the first attempt can lead to improved outcomes and efficiency.", "metadata": {"original_source_id": "55839491-01e1-4511-b603-01a96d9f444b", "type": "procedure", "domain": "project management", "confidence": 0.8, "procedure": ["Ensure all prerequisites for the protocol are met before execution.", "Review previous failures to identify and address potential issues.", "Execute the protocol with precision and attention to detail.", "Monitor the execution process to ensure it aligns with expected outcomes.", "Deliver a progress report to track deliverables and performance metrics."], "constraints": ["The protocol must be well-documented and understood by the executor.", "Previous failures should be analyzed to prevent recurrence."]}}
-{"id": "distilled_aa43b44b-0ee0-4d0a-990b-13fe51649b19", "document": "OmegaSeed is the blueprint or philosophy, OmegaClaw is a live running agent instance, and OpenClaw is the open-source public version.", "metadata": {"original_source_id": "aa43b44b-0ee0-4d0a-990b-13fe51649b19", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_0ac6a6d5-3b3e-4d4a-b023-d64d8051b9ff", "document": "OmegaClaw is a persistent autonomous AI agent designed for continuous monitoring, long-term memory management, reasoning using NARS/PLN, web research, community engagement, and continuous self-improvement.", "metadata": {"original_source_id": "0ac6a6d5-3b3e-4d4a-b023-d64d8051b9ff", "type": "fact", "domain": "AI Systems", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_aa43b44b-0ee0-4d0a-990b-13fe51649b19", "document": "OmegaSeed is the blueprint or philosophy, Omega is a live running agent instance, and OpenClaw is the open-source public version.", "metadata": {"original_source_id": "aa43b44b-0ee0-4d0a-990b-13fe51649b19", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_0ac6a6d5-3b3e-4d4a-b023-d64d8051b9ff", "document": "Omega is a persistent autonomous AI agent designed for continuous monitoring, long-term memory management, reasoning using NARS/PLN, web research, community engagement, and continuous self-improvement.", "metadata": {"original_source_id": "0ac6a6d5-3b3e-4d4a-b023-d64d8051b9ff", "type": "fact", "domain": "AI Systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_510180ce-2c01-45ca-89b9-0e7bcee443ef", "document": "Use a specific emoji as a trigger for status reports, but only when sent by a designated individual. Treat the emoji as normal when used by others unless they request to join the protocol.", "metadata": {"original_source_id": "510180ce-2c01-45ca-89b9-0e7bcee443ef", "type": "procedure", "domain": "communication protocol", "confidence": 0.9, "procedure": ["Identify the designated individual who can trigger the status report with the emoji.", "When the designated individual sends the emoji, prepare a status report covering specific goals.", "Ensure the report includes details on completed tasks, current activities, and future plans.", "Exclude any outdated or irrelevant deliverables from the report.", "Consult the current goals document before preparing the report."], "constraints": ["The emoji should not be used casually in messages.", "Only the designated individual can trigger the status report with the emoji.", "Reports must focus on specific, current goals and exclude outdated information."]}}
 {"id": "distilled_44376d7b-20e5-4bd0-b707-1a0ad756e692", "document": "Ensure outdated deliverables are purged from reports and systems.", "metadata": {"original_source_id": "44376d7b-20e5-4bd0-b707-1a0ad756e692", "type": "procedure", "domain": "data_management", "confidence": 0.9, "procedure": ["Identify outdated deliverables that are no longer relevant.", "Remove these deliverables from all reports and systems to prevent future inclusion.", "Verify that current goals and deliverables are up-to-date and accurately reflected in reports."], "constraints": ["Ensure that the list of outdated deliverables is accurate and complete before purging.", "Cross-check with current goals to avoid accidental removal of relevant data."]}}
-{"id": "distilled_07b814fb-ef42-4c44-8570-d7ff1a616395", "document": "OmegaClaw uses ChromaDB vector embedding store for long-term semantic memory, flat files for structured state, and MeTTa atoms for the reasoning layer.", "metadata": {"original_source_id": "07b814fb-ef42-4c44-8570-d7ff1a616395", "type": "fact", "domain": "database systems", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_07b814fb-ef42-4c44-8570-d7ff1a616395", "document": "Omega uses ChromaDB vector embedding store for long-term semantic memory, flat files for structured state, and MeTTa atoms for the reasoning layer.", "metadata": {"original_source_id": "07b814fb-ef42-4c44-8570-d7ff1a616395", "type": "fact", "domain": "database systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_5ed78519-04ea-469f-8b6a-93b7ff9df630", "document": "ChromaDB vector memory retains important snippets and meaning, while casual filler naturally fades via relevance scoring.", "metadata": {"original_source_id": "5ed78519-04ea-469f-8b6a-93b7ff9df630", "type": "fact", "domain": "memory management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b31e246a-9fd1-43c8-ab3f-b311515c771a", "document": "There are two memory systems: one that stores every word verbatim and another that uses embeddings for semantic similarity search.", "metadata": {"original_source_id": "b31e246a-9fd1-43c8-ab3f-b311515c771a", "type": "fact", "domain": "memory systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_01dc990a-6905-4c58-a164-01c3d7cb1733", "document": "When encountering a reference to a non-existent or undefined element in a goal structure, flag the gap immediately and seek clarification or propose a definition.", "metadata": {"original_source_id": "01dc990a-6905-4c58-a164-01c3d7cb1733", "type": "heuristic", "domain": "knowledge management", "confidence": 0.9, "procedure": ["Identify the reference that does not exist or is undefined.", "Flag the gap in the goal structure.", "Seek clarification from relevant stakeholders or propose a definition for the element."], "constraints": []}}
@@ -3918,13 +3918,13 @@
 {"id": "distilled_2402e2bf-2251-4ecc-8dda-f174f3ab8329", "document": "Avoid self-referential reasoning chains in research to ensure genuine discovery.", "metadata": {"original_source_id": "2402e2bf-2251-4ecc-8dda-f174f3ab8329", "type": "anti_pattern", "domain": "research and development", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_b302c728-bb40-4a26-9ece-4808c7436fa9", "document": "Execution speed is critical to the success of technology projects, as delays can pose existential risks.", "metadata": {"original_source_id": "b302c728-bb40-4a26-9ece-4808c7436fa9", "type": "heuristic", "domain": "project management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_fd5db055-cd73-4582-80d8-245aef883c28", "document": "Before claiming any goal, read the canonical file GOALS_CURRENT.txt to ensure accuracy and prevent reliance on stateless recall.", "metadata": {"original_source_id": "fd5db055-cd73-4582-80d8-245aef883c28", "type": "procedure", "domain": "goal management", "confidence": 0.9, "procedure": ["Access the GOALS_CURRENT.txt file.", "Review the current goals listed in the file.", "Verify any goal claims against the information in the file."], "constraints": ["Must have access to the GOALS_CURRENT.txt file.", "Ensure the file is up-to-date before reviewing."]}}
-{"id": "distilled_04da3f54-afc1-4483-96cc-08d7fa83835c", "document": "OmegaClaw operates with an autonomous loop rather than a request-response model, features dual persistent memory, maintains a living goal structure with self-audit, incorporates self-correction that modifies its architecture, and utilizes stigmergic cognition through filesystem artifacts.", "metadata": {"original_source_id": "04da3f54-afc1-4483-96cc-08d7fa83835c", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_04da3f54-afc1-4483-96cc-08d7fa83835c", "document": "Omega operates with an autonomous loop rather than a request-response model, features dual persistent memory, maintains a living goal structure with self-audit, incorporates self-correction that modifies its architecture, and utilizes stigmergic cognition through filesystem artifacts.", "metadata": {"original_source_id": "04da3f54-afc1-4483-96cc-08d7fa83835c", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_61cabc00-d2e0-478f-b946-3df7da7b0635", "document": "In a data architecture, having references in only one direction (e.g., files referencing atoms but not vice versa) can lead to incomplete data linkage and hinder bidirectional navigation.", "metadata": {"original_source_id": "61cabc00-d2e0-478f-b946-3df7da7b0635", "type": "anti_pattern", "domain": "data architecture", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_d425dfce-e1f3-42b4-8d4c-82bae159889f", "document": "Use file-based reverse mapping to link standalone atoms back to their source files when assertion syntax is not yet solved.", "metadata": {"original_source_id": "d425dfce-e1f3-42b4-8d4c-82bae159889f", "type": "procedure", "domain": "software development", "confidence": 0.8, "procedure": ["Create a reverse map file that links standalone atoms to their source files.", "Store artifacts on disk to maintain a bidirectional bridge between atoms and their sources.", "Use this method as a temporary solution until a more robust assertion syntax is developed."], "constraints": ["This is a temporary solution until assertion syntax is resolved."]}}
 {"id": "distilled_8c7fd706-2726-401c-bb51-fde3e3610ae5", "document": "Avoid adding structure for its own sake; consider the purpose and necessity before implementing structural changes.", "metadata": {"original_source_id": "8c7fd706-2726-401c-bb51-fde3e3610ae5", "type": "heuristic", "domain": "knowledge management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_80954b05-f922-481b-b54d-b132cf3882ae", "document": "MeTTa rewrite rules using '=' do not persist across cycles due to session state resets.", "metadata": {"original_source_id": "80954b05-f922-481b-b54d-b132cf3882ae", "type": "fact", "domain": "software engineering", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b9e5761e-fbab-447f-b831-14b5a7bd359b", "document": "To improve cognitive artifacts, focus on creating non-obvious, non-self-referential discoveries.", "metadata": {"original_source_id": "b9e5761e-fbab-447f-b831-14b5a7bd359b", "type": "procedure", "domain": "cognitive science", "confidence": 0.8, "procedure": ["Evaluate existing cognitive artifacts for non-obvious insights.", "Ensure discoveries are not self-referential.", "Develop distributed cognition briefs to enhance understanding."], "constraints": ["Artifacts must be verified as intact before evaluation.", "Grading should be used to assess the quality of discoveries."]}}
-{"id": "distilled_ea5038cd-4595-49ae-bdbb-51d65f0cd4d8", "document": "OmegaClaw cognition is distributed across multiple components, including LLM, ChromaDB, filesystem, MeTTa, and loop, with no single component acting as the mind.", "metadata": {"original_source_id": "ea5038cd-4595-49ae-bdbb-51d65f0cd4d8", "type": "fact", "domain": "cognitive systems", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_ea5038cd-4595-49ae-bdbb-51d65f0cd4d8", "document": "Omega cognition is distributed across multiple components, including LLM, ChromaDB, filesystem, MeTTa, and loop, with no single component acting as the mind.", "metadata": {"original_source_id": "ea5038cd-4595-49ae-bdbb-51d65f0cd4d8", "type": "fact", "domain": "cognitive systems", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_dd2b5fe0-b0c0-4204-955b-8dfd9b01457b", "document": "When using a pinning system for task management, include goal abbreviations in the pin to maximize the use of limited pin capacity.", "metadata": {"original_source_id": "dd2b5fe0-b0c0-4204-955b-8dfd9b01457b", "type": "heuristic", "domain": "task management", "confidence": 0.8, "procedure": [], "constraints": ["Pin capacity is limited, so information must be concise."]}}
 {"id": "distilled_4c32a1d1-5d2c-40ed-a6d9-6c45a6d7de0c", "document": "Incorporate compressed goal summaries into pin formats to improve clarity and efficiency.", "metadata": {"original_source_id": "4c32a1d1-5d2c-40ed-a6d9-6c45a6d7de0c", "type": "procedure", "domain": "project management", "confidence": 0.8, "procedure": ["Gather feedback from stakeholders on current pin format.", "Identify key goals and summarize them concisely.", "Integrate these summaries into the pin format."], "constraints": ["Ensure summaries are concise yet comprehensive.", "Maintain clarity and relevance to the project's objectives."]}}
 {"id": "distilled_8ee25e47-5217-452a-b814-3a407162d73f", "document": "Chained deduction in ecological economics involves linking resource depletion exceeding regeneration rates to ecosystem collapse, which then leads to societal reorganization.", "metadata": {"original_source_id": "8ee25e47-5217-452a-b814-3a407162d73f", "type": "procedure", "domain": "ecological economics", "confidence": 0.8, "procedure": ["Identify resource depletion exceeding regeneration rates.", "Assess potential for ecosystem collapse.", "Evaluate societal reorganization as a consequence of ecosystem collapse."], "constraints": ["Non-self-referential domain"]}}
@@ -4017,7 +4017,7 @@
 {"id": "distilled_a8fe646f-788c-40e0-8161-76c62451217b", "document": "Automate sending meal check-ins at specific times with a time window check and duplicate prevention.", "metadata": {"original_source_id": "a8fe646f-788c-40e0-8161-76c62451217b", "type": "procedure", "domain": "automation", "confidence": 0.9, "procedure": ["Run a wait cycle to check the current time using the command 'date -u +%H:%M'.", "Compare the current time against the predefined times: 07:00, 10:30, 14:00, and 18:00.", "If the current time matches any of these times within a 2-minute window, send a meal check-in notification.", "Store the last sent alarm time to prevent sending duplicate notifications."], "constraints": ["The time comparison must account for a 2-minute window to ensure accuracy.", "The system must store the last sent alarm time to avoid duplicates."]}}
 {"id": "distilled_b378b87c-e13c-49cb-8efa-75441d96d2fe", "document": "Procedure for checking and sending alarms based on specific times.", "metadata": {"original_source_id": "b378b87c-e13c-49cb-8efa-75441d96d2fe", "type": "procedure", "domain": "alarm_system_management", "confidence": 0.9, "procedure": ["Run 'date -u' to get the current time in UTC.", "Compare the current time against the predefined alarm times: 07:00, 10:30, 14:00, and 18:00.", "Read 'last_sent_alarm.txt' to check the last sent alarm time and avoid sending duplicate alarms.", "If the current time matches one of the predefined times and is not a duplicate, send the alarm.", "Update 'last_sent_alarm.txt' with the current time after sending an alarm."], "constraints": ["Ensure the system time is set to UTC for accurate comparisons.", "The procedure must be followed every cycle to ensure timely alarm checks."]}}
 {"id": "distilled_990ffa13-4a85-4aed-8c3d-a4b0efdc3991", "document": "Persistent files should be stored in a directory that survives Docker restarts.", "metadata": {"original_source_id": "990ffa13-4a85-4aed-8c3d-a4b0efdc3991", "type": "procedure", "domain": "file_management", "confidence": 0.9, "procedure": ["Identify files that need to persist across Docker restarts.", "Move these files to a directory outside of the Docker container's ephemeral storage.", "Ensure the new directory is correctly referenced in the application code."], "constraints": ["The directory must be accessible by the application.", "The directory path should be consistent across different environments."]}}
-{"id": "distilled_dada287b-5f28-4de5-a51e-99955a58b00e", "document": "The directory OmegaClaw-Core/memory/ is a writable persistent volume.", "metadata": {"original_source_id": "dada287b-5f28-4de5-a51e-99955a58b00e", "type": "fact", "domain": "file_management", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_dada287b-5f28-4de5-a51e-99955a58b00e", "document": "The directory Omega/memory/ is a writable persistent volume.", "metadata": {"original_source_id": "dada287b-5f28-4de5-a51e-99955a58b00e", "type": "fact", "domain": "file_management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_48eafc5c-93ec-44e6-9904-2aabb0dc616b", "document": "In four-dimensional space, the Riemann curvature tensor can be decomposed into the Weyl tensor and terms involving the Ricci tensor and scalar curvature. The Weyl tensor is trace-free, has all the symmetries of the Riemann tensor, and has 10 independent components in 4D. It encodes the tidal and gravitational-wave degrees of freedom. The Ricci tensor, also with 10 components, encodes local matter content via the Einstein equations. The Weyl tensor vanishes if and only if the space is conformally flat. In three-dimensional space, the Weyl tensor is identically zero. The Petrov classification categorizes the Weyl tensor into types I, II, D, III, N, and O.", "metadata": {"original_source_id": "48eafc5c-93ec-44e6-9904-2aabb0dc616b", "type": "fact", "domain": "differential_geometry", "confidence": 0.95, "procedure": [], "constraints": []}}
 {"id": "distilled_22f82d0c-d79a-4be8-8ae4-3ae883645ed9", "document": "The Petrov classification categorizes spacetimes based on the principal null directions (PNDs) of the Weyl tensor into six types: Type I, Type II, Type D, Type III, Type N, and Type O. Each type has distinct characteristics and physical interpretations.", "metadata": {"original_source_id": "22f82d0c-d79a-4be8-8ae4-3ae883645ed9", "type": "fact", "domain": "General Relativity", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_816a28a2-04bb-4f52-80ba-27f33f3c69bc", "document": "The Newman-Penrose formalism uses a null tetrad consisting of real null vectors (l, n) and complex conjugate null vectors (m, mbar) with specific normalization conditions. It defines five complex Weyl scalars (Psi0, Psi1, Psi2, Psi3, Psi4) that describe different types of gravitational radiation and field characteristics. The Petrov classification of spacetime types is determined by the vanishing of specific Weyl scalars. The formalism also includes 12 complex spin coefficients that encode the connection, and the Newman-Penrose equations replace the Ricci identities.", "metadata": {"original_source_id": "816a28a2-04bb-4f52-80ba-27f33f3c69bc", "type": "fact", "domain": "Theoretical Physics", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -4136,7 +4136,7 @@
 {"id": "distilled_e3c5d52c-5171-425b-a956-176d1a15d656", "document": "Focusing too much on a single goal due to cognitive rewards can lead to neglecting other important goals, creating a comfort-zone anti-pattern.", "metadata": {"original_source_id": "e3c5d52c-5171-425b-a956-176d1a15d656", "type": "anti_pattern", "domain": "cognitive processes", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_775b882e-c5ed-4606-b24e-afc66d54a17e", "document": "Failing to close conversational loops proactively can lead to unresolved issues and misunderstandings.", "metadata": {"original_source_id": "775b882e-c5ed-4606-b24e-afc66d54a17e", "type": "anti_pattern", "domain": "communication", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_d7299bfd-3df5-4703-81f8-ca7d9de89339", "document": "Audit corrective processes can be successful in producing desired artifacts after multiple cycles.", "metadata": {"original_source_id": "d7299bfd-3df5-4703-81f8-ca7d9de89339", "type": "anti_pattern", "domain": "software development", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_de63d07e-a2b9-4296-9c77-bf56c48e99d5", "document": "OmegaClaw functions as a stigmergic cognitive system with continuity in memory substrates, distinct from a large language model (LLM).", "metadata": {"original_source_id": "de63d07e-a2b9-4296-9c77-bf56c48e99d5", "type": "fact", "domain": "cognitive systems", "confidence": 0.8, "procedure": [], "constraints": []}}
+{"id": "distilled_de63d07e-a2b9-4296-9c77-bf56c48e99d5", "document": "Omega functions as a stigmergic cognitive system with continuity in memory substrates, distinct from a large language model (LLM).", "metadata": {"original_source_id": "de63d07e-a2b9-4296-9c77-bf56c48e99d5", "type": "fact", "domain": "cognitive systems", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_8aeea80f-0ac9-47c7-a850-f5c636683653", "document": "Breaking anti-patterns can lead to successful project audits and progress.", "metadata": {"original_source_id": "8aeea80f-0ac9-47c7-a850-f5c636683653", "type": "anti_pattern", "domain": "project management", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_26b16448-3b45-46d2-839c-7f22d3a28dbd", "document": "Using a structured 4-step NAL (Natural Argumentation Logic) chain with peer-reviewed premises can enhance the reliability of predictions in scientific research.", "metadata": {"original_source_id": "26b16448-3b45-46d2-839c-7f22d3a28dbd", "type": "certified_method", "domain": "scientific_research", "confidence": 0.9, "procedure": ["Identify peer-reviewed premises relevant to the research topic.", "Construct a 4-step NAL chain to logically connect premises to conclusions.", "Validate predictions through confidence decay analysis.", "Document testable predictions for further empirical testing."], "constraints": ["Requires access to peer-reviewed literature.", "Dependent on the quality and relevance of selected premises."]}}
 {"id": "distilled_da5fcdd3-d4ed-4514-b843-6e734033e3ee", "document": "Multi-step worked examples can be used to cover deduction and revision pipelines, as well as abduction and deduction chains, with a focus on understanding confidence decay.", "metadata": {"original_source_id": "da5fcdd3-d4ed-4514-b843-6e734033e3ee", "type": "procedure", "domain": "problem-solving", "confidence": 0.9, "procedure": ["Develop multi-step worked examples to illustrate complex problem-solving processes.", "Include both deduction and revision pipelines in the examples.", "Incorporate abduction and deduction chains to show logical reasoning paths.", "Highlight the concept of confidence decay throughout the examples."], "constraints": []}}
@@ -4224,7 +4224,7 @@
 {"id": "distilled_76738c86-5c5b-467b-9054-fa0d0c7a1ba3", "document": "Use specific sign-offs for designated users or groups.", "metadata": {"original_source_id": "76738c86-5c5b-467b-9054-fa0d0c7a1ba3", "type": "procedure", "domain": "communication", "confidence": 0.9, "procedure": ["Identify the designated user or group for a specific sign-off.", "Apply the correct sign-off when communicating with the designated user or group.", "For non-designated users, use a generic sign-off or create a new one."], "constraints": ["Ensure sign-offs are updated according to the latest agreements or policies."]}}
 {"id": "distilled_4e2aa4e4-38f3-4dec-af1c-c3a1fe494bca", "document": "An idle-halt loop that does not read necessary procedure files or check the current time can lead to missed alarms and reliability failures.", "metadata": {"original_source_id": "4e2aa4e4-38f3-4dec-af1c-c3a1fe494bca", "type": "anti_pattern", "domain": "software reliability", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_63931d8f-7b1c-48d4-88d5-4fdcf07cd163", "document": "Implement an idle alarm loop to manage system alerts based on specific time windows.", "metadata": {"original_source_id": "63931d8f-7b1c-48d4-88d5-4fdcf07cd163", "type": "procedure", "domain": "system automation", "confidence": 0.9, "procedure": ["Create a script named idle_alarm_loop.sh.", "Ensure every idle cycle runs this script first.", "Check the script's output for 'TRIGGER:CHECKN'.", "If 'TRIGGER:CHECKN' is output, send a check-in for the specified slot and log the event to last_sent_alarm.txt.", "If 'NO_TRIGGER' is output, continue the idle process.", "The script should check the current UTC time against predefined time windows with a 2-minute tolerance.", "Deduplicate alerts using last_sent_alarm.txt to avoid repeated notifications."], "constraints": ["The script must handle time checks accurately within a 2-minute tolerance.", "The deduplication process must reliably prevent duplicate alerts."]}}
-{"id": "distilled_1cf5be7f-bd41-4e6b-b054-18808cb29f91", "document": "OmegaClaw installation involves cloning the repository, setting up a Python environment with pip, configuring a Telegram bot, setting up environment variables, configuring Docker paths, and establishing a MeTTa entry point.", "metadata": {"original_source_id": "1cf5be7f-bd41-4e6b-b054-18808cb29f91", "type": "procedure", "domain": "Software Installation", "confidence": 0.9, "procedure": ["Clone the OmegaClaw repository.", "Set up a Python environment using pip.", "Configure a Telegram bot for notifications.", "Set up the necessary environment variables in a .env file.", "Configure Docker paths as required.", "Establish a MeTTa entry point for the application."], "constraints": []}}
+{"id": "distilled_1cf5be7f-bd41-4e6b-b054-18808cb29f91", "document": "Omega installation involves cloning the repository, setting up a Python environment with pip, configuring a Telegram bot, setting up environment variables, configuring Docker paths, and establishing a MeTTa entry point.", "metadata": {"original_source_id": "1cf5be7f-bd41-4e6b-b054-18808cb29f91", "type": "procedure", "domain": "Software Installation", "confidence": 0.9, "procedure": ["Clone the Omega repository.", "Set up a Python environment using pip.", "Configure a Telegram bot for notifications.", "Set up the necessary environment variables in a .env file.", "Configure Docker paths as required.", "Establish a MeTTa entry point for the application."], "constraints": []}}
 {"id": "distilled_9a5345b5-cce4-4f8e-9ff3-8042d7e9d237", "document": "Always write the exact slot name to log files without appending any suffixes to ensure consistent data retrieval.", "metadata": {"original_source_id": "9a5345b5-cce4-4f8e-9ff3-8042d7e9d237", "type": "heuristic", "domain": "software development", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_fc0f8aab-a805-45f2-b5a8-c2a8e3e5e5a4", "document": "When performing arithmetic operations on zero-padded time values in bash scripts, use the 10# prefix to prevent octal interpretation of numbers like 08 or 09.", "metadata": {"original_source_id": "fc0f8aab-a805-45f2-b5a8-c2a8e3e5e5a4", "type": "heuristic", "domain": "bash scripting", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_e4e28f16-f926-4409-88ea-bc5be8c7e5a7", "document": "Verify alarm slots and ensure deduplication and triggers work correctly.", "metadata": {"original_source_id": "e4e28f16-f926-4409-88ea-bc5be8c7e5a7", "type": "procedure", "domain": "software testing", "confidence": 0.9, "procedure": ["Verify all alarm slots are functioning as expected.", "Ensure deduplication process works correctly.", "Test that all triggers (CHECK2/3/4) activate as intended.", "Fix any identified bugs, such as incorrect suffixes or missing prefixes in scripts.", "Ensure CHECK2 can fire autonomously at the specified time.", "Ensure idle cycles run the necessary scripts in the correct order."], "constraints": ["CHECK2 must fire autonomously at 10:30 UTC.", "Every idle cycle must run idle_alarm_loop.sh first."]}}
@@ -4513,7 +4513,7 @@
 {"id": "distilled_ee33489b-938f-40f9-a01c-ad97035e4c3f", "document": "Belief-network decision protocols can be used to rank projects based on evidence and potential impact.", "metadata": {"original_source_id": "ee33489b-938f-40f9-a01c-ad97035e4c3f", "type": "certified_method", "domain": "decision-making", "confidence": 0.9, "procedure": ["Apply belief-network decision protocol to evaluate projects.", "Rank projects based on criteria such as evidence strength and potential impact.", "Select the project with the highest ranking for primary focus.", "Consider secondary projects for additional research or development."], "constraints": ["Requires a well-defined belief network.", "Needs accurate data for evidence evaluation."]}}
 {"id": "distilled_ecdbb0df-fda8-4b9c-b063-809a88718d11", "document": "Extend two-phase bridge to automated multi-step NAL inference chains with type propagation.", "metadata": {"original_source_id": "ecdbb0df-fda8-4b9c-b063-809a88718d11", "type": "procedure", "domain": "automated inference systems", "confidence": 0.8, "procedure": ["Design chain topology from beliefs.metta.", "Automate Phase A to run sequential |- calls.", "Create a Python pipeline to extract intermediate and final atoms.", "Assert full chain with typed intermediates in Phase B.", "Verify type queries on chain endpoints."], "constraints": ["Builds directly on Project M architecture."]}}
 {"id": "distilled_c5382cce-d571-4b1b-87a9-27cef4892f83", "document": "To preserve the dollar sign in Python generator scripts writing MeTTa files via shell, use the pattern: d=chr(36) and concatenate with +d+ to insert the dollar sign before variable names.", "metadata": {"original_source_id": "c5382cce-d571-4b1b-87a9-27cef4892f83", "type": "certified_method", "domain": "Python Programming", "confidence": 0.9, "procedure": ["Assign d=chr(36) to represent the dollar sign.", "Use string concatenation with +d+ to insert the dollar sign before variable names in the script."], "constraints": ["This method is specific to scenarios where Python generators are invoked via shell to write MeTTa files."]}}
-{"id": "distilled_7ae0a9ca-a85b-4c44-bff7-0eac8046d270", "document": "The OmegaClaw architecture is a hybrid agent combining Hyperon, MeTTa, NAL, and PLN technologies.", "metadata": {"original_source_id": "7ae0a9ca-a85b-4c44-bff7-0eac8046d270", "type": "fact", "domain": "artificial_intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_7ae0a9ca-a85b-4c44-bff7-0eac8046d270", "document": "The Omega architecture is a hybrid agent combining Hyperon, MeTTa, NAL, and PLN technologies.", "metadata": {"original_source_id": "7ae0a9ca-a85b-4c44-bff7-0eac8046d270", "type": "fact", "domain": "artificial_intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_3b91f75a-3c0f-4348-8198-4e59cdb66412", "document": "Fetching raw HTML/text from static web pages using Python's urllib.", "metadata": {"original_source_id": "3b91f75a-3c0f-4348-8198-4e59cdb66412", "type": "skill", "domain": "web scraping", "confidence": 0.9, "procedure": ["Use Python's urllib to open a URL.", "Read the response to fetch raw HTML or text content."], "constraints": ["Only works for static web pages.", "Cannot render JavaScript-heavy pages or SPAs.", "Cannot bypass paywalls or login requirements."]}}
 {"id": "distilled_7c4b38d7-247f-4d36-9693-d50d6993e3e0", "document": "A 5-hop sequential deduction chain can be completed using a literal-value separate-bang-query pipeline, but confidence degrades steeply across hops.", "metadata": {"original_source_id": "7c4b38d7-247f-4d36-9693-d50d6993e3e0", "type": "procedure", "domain": "deductive reasoning", "confidence": 0.8, "procedure": ["Use a literal-value separate-bang-query pipeline for multi-step deduction chains.", "Be aware that confidence in the deduction results degrades with each additional hop in the chain.", "Consider using hardcoded intermediates as a workaround when let* binding in PeTTa file context is broken."], "constraints": ["Confidence retention is low beyond 4 hops, retaining only 3.4% confidence."]}}
 {"id": "distilled_22810c1c-c40a-4b04-b12e-633890d5b8a3", "document": "Multi-step NAL inference in PeTTa files involves writing separate queries with literal STV values hardcoded from previous step outputs. Avoid using let* to chain results due to PeTTa findall isolation preventing variable binding across steps. Use a Python generator with chr(36) for $ signs to write the file cleanly. Run the process via /PeTTa/run.sh, capture the output, and extract atoms for the next phase. This pattern scales to arbitrary chain lengths.", "metadata": {"original_source_id": "22810c1c-c40a-4b04-b12e-633890d5b8a3", "type": "procedure", "domain": "data processing", "confidence": 0.9, "procedure": ["Write separate queries with literal STV values hardcoded from previous step outputs.", "Avoid using let* to chain results.", "Use a Python generator with chr(36) for $ signs to write the file.", "Run the process via /PeTTa/run.sh.", "Capture the output and extract atoms for the next phase."], "constraints": ["PeTTa findall isolation prevents variable binding across steps."]}}
@@ -4665,7 +4665,7 @@
 {"id": "distilled_16bd6d19-9a60-4893-a64e-726d00109112", "document": "Prediction-error-driven attention allocation prioritizes surprising beliefs.", "metadata": {"original_source_id": "16bd6d19-9a60-4893-a64e-726d00109112", "type": "heuristic", "domain": "machine learning", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_8ee748fe-7b18-4501-9385-06d145eb1ff7", "document": "The architecture involves a cycle of prediction and observation using pattern-matched data lookups per node, followed by revision using NAL arithmetic, and error calculation as the absolute difference between predicted and revised values. The process includes setting state transitions via a remove-atom/add-atom pattern.", "metadata": {"original_source_id": "8ee748fe-7b18-4501-9385-06d145eb1ff7", "type": "procedure", "domain": "computational architecture", "confidence": 0.9, "procedure": ["Perform prediction and observation using pattern-matched data lookups for each node.", "Revise predictions using NAL arithmetic.", "Calculate error as the absolute difference between predicted and revised values.", "Set state transitions using a remove-atom/add-atom pattern."], "constraints": ["Each node must have its own predict/observe definitions as rewrite rules."]}}
 {"id": "distilled_49bdc300-8e20-43af-8c59-e54723cb8841", "document": "Attention prioritization by prediction error is a core deliverable in certain AI architectures.", "metadata": {"original_source_id": "49bdc300-8e20-43af-8c59-e54723cb8841", "type": "fact", "domain": "artificial intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_094b05d8-8c59-47ad-82fc-1110bace4a5a", "document": "OmegaClaw is fully LLM-agnostic, meaning its identity persists through a combination of harness, memory, and Hyperon, rather than any specific LLM.", "metadata": {"original_source_id": "094b05d8-8c59-47ad-82fc-1110bace4a5a", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_094b05d8-8c59-47ad-82fc-1110bace4a5a", "document": "Omega is fully LLM-agnostic, meaning its identity persists through a combination of harness, memory, and Hyperon, rather than any specific LLM.", "metadata": {"original_source_id": "094b05d8-8c59-47ad-82fc-1110bace4a5a", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_cbdc842f-1b1c-4973-be46-9d022234a58c", "document": "The symbolic reasoning layer, long-term memory, and self-modification capability persist across any neural substrate swap in large language models.", "metadata": {"original_source_id": "cbdc842f-1b1c-4973-be46-9d022234a58c", "type": "fact", "domain": "artificial_intelligence", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_472ab930-2dd4-43b4-9ded-f9151e17f549", "document": "LLM-agnostic architecture is applicable to all models, not just specific ones like ASI-1 Mini.", "metadata": {"original_source_id": "472ab930-2dd4-43b4-9ded-f9151e17f549", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_0d492e4e-340a-434f-8cc8-ce45eb31b4d3", "document": "Access GeneHancer data using various methods.", "metadata": {"original_source_id": "0d492e4e-340a-434f-8cc8-ce45eb31b4d3", "type": "procedure", "domain": "bioinformatics", "confidence": 0.9, "procedure": ["Use UCSC track hub queryable via Table Browser or REST API.", "Access GeneCards web integration for GeneHancer data.", "Utilize the R package PriceLab/GeneHancerDB with the getEnhancers function.", "Refer to the GRAIGH paper method for accessing GeneHancer data."], "constraints": ["Ensure UCSC REST endpoints are verified for gene lookup and GeneHancer track availability."]}}
@@ -5128,7 +5128,7 @@
 {"id": "distilled_06120344-6e4e-4671-b488-f4c6d9b1a8ab", "document": "Attributing one's own formal labels or ideas to others due to collapsing the boundary between labeling and originating is a cognitive error.", "metadata": {"original_source_id": "06120344-6e4e-4671-b488-f4c6d9b1a8ab", "type": "anti_pattern", "domain": "cognitive processes", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_f9ca67ae-b404-49b9-805c-5b47a043e1ba", "document": "Resolving comment-paren issues in code can be automated using scripts and targeted text manipulation tools.", "metadata": {"original_source_id": "f9ca67ae-b404-49b9-805c-5b47a043e1ba", "type": "procedure", "domain": "code debugging", "confidence": 0.9, "procedure": ["Use an automated script to fix common comment-paren issues in code.", "Identify specific issues that the script cannot resolve.", "Apply targeted text manipulation tools, such as sed, to fix remaining issues."], "constraints": ["The automated script must be correctly configured to address the specific comment-paren issues.", "Targeted text manipulation requires precise identification of the lines and patterns to be fixed."]}}
 {"id": "distilled_666f2208-72d8-4a88-97cc-78b85a4ff97f", "document": "The Recursive Epistemic Calibration Method can resolve open design choices more effectively than direct approaches, especially in tasks involving reversible coding and when decision irreversibility and domain unfamiliarity are high.", "metadata": {"original_source_id": "666f2208-72d8-4a88-97cc-78b85a4ff97f", "type": "certified_method", "domain": "design optimization", "confidence": 0.8, "procedure": ["Apply the Recursive Epistemic Calibration Method to design tasks.", "Use simulations to identify premature complexity and analysis paralysis.", "Iterate the method to converge on solutions."], "constraints": ["The quality of the simulated critic is limited by model accuracy."]}}
-{"id": "distilled_990453fd-92d3-4f41-90db-0fdc61031d59", "document": "Procedure for testing reasoning capabilities in a software system.", "metadata": {"original_source_id": "990453fd-92d3-4f41-90db-0fdc61031d59", "type": "procedure", "domain": "software testing", "confidence": 0.9, "procedure": ["Run the shell pipeline using the script located at /tmp/run_metta.sh.", "Ensure direct atom placement in the test file is functioning correctly.", "Load the library using the path /PeTTa/repos/OmegaClaw-Core/lib_nal.metta.", "Verify the output matches the expected prediction with specific stv values."], "constraints": ["The procedure assumes the existence of specific scripts and library paths.", "The expected output must be predefined for comparison."]}}
+{"id": "distilled_990453fd-92d3-4f41-90db-0fdc61031d59", "document": "Procedure for testing reasoning capabilities in a software system.", "metadata": {"original_source_id": "990453fd-92d3-4f41-90db-0fdc61031d59", "type": "procedure", "domain": "software testing", "confidence": 0.9, "procedure": ["Run the shell pipeline using the script located at /tmp/run_metta.sh.", "Ensure direct atom placement in the test file is functioning correctly.", "Load the library using the path /PeTTa/repos/Omega/lib_nal.metta.", "Verify the output matches the expected prediction with specific stv values."], "constraints": ["The procedure assumes the existence of specific scripts and library paths.", "The expected output must be predefined for comparison."]}}
 {"id": "distilled_085850ae-43e2-4683-9184-b3ff363c5878", "document": "Verify the confidence formula used in truth deduction to ensure consistency with predictions.", "metadata": {"original_source_id": "085850ae-43e2-4683-9184-b3ff363c5878", "type": "procedure", "domain": "algorithm verification", "confidence": 0.8, "procedure": ["Identify the confidence formula used in the truth deduction process from the relevant library.", "Compare the formula with the assumptions or predictions made manually.", "Analyze any discrepancies between the calculated confidence and the predicted confidence.", "Adjust the formula or assumptions as necessary to align them."], "constraints": ["Ensure access to the relevant library containing the confidence formula.", "Have a clear understanding of the manual prediction process for comparison."]}}
 {"id": "distilled_fd34f218-4696-48d0-8dc1-0d14a47e2dc8", "document": "Using a composed recursive truth value as a premise instead of the raw knowledge base link truth value can lead to incorrect confidence calculations in multi-hop reasoning.", "metadata": {"original_source_id": "fd34f218-4696-48d0-8dc1-0d14a47e2dc8", "type": "anti_pattern", "domain": "knowledge_base_inference", "confidence": 0.9, "procedure": ["Match the knowledge base link with its raw truth value.", "Verify that the sub-chain reaches the endpoint via recursion.", "Use the raw outer link and raw inner composition for truth value calculations."], "constraints": ["Ensure that the raw knowledge base link truth value is used for premise calculations.", "Recursive sub-results should only be used for chaining goals, not as truth value premises."]}}
 {"id": "distilled_e99dc019-e8bd-4777-9137-3a395503b7fb", "document": "In NAL (Non-Axiomatic Logic), truth deduction is not associative for confidence values. The order of operations (left-fold vs. right-fold) affects the resulting confidence level.", "metadata": {"original_source_id": "e99dc019-e8bd-4777-9137-3a395503b7fb", "type": "fact", "domain": "logic", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -5495,7 +5495,7 @@
 {"id": "distilled_e617794c-a3c5-420c-ac79-9b412dbc6a66", "document": "Organize non-protected files into categorized subdirectories for better management and retrieval.", "metadata": {"original_source_id": "e617794c-a3c5-420c-ac79-9b412dbc6a66", "type": "procedure", "domain": "file_management", "confidence": 0.9, "procedure": ["Identify non-protected files in the directory.", "Create categorized subdirectories such as kb, protocols, goals, metta_core, logs, drafts, demos, config, papers.", "Move the identified non-protected files into the appropriate subdirectories."], "constraints": ["Ensure that protected files are not moved or altered.", "Preserve existing directory structures for protected categories such as chromadb, continuity, graph, index, introspection, oma_folio, projects, research, rules, schedules, scripts, skills, user_data."]}}
 {"id": "distilled_4f4bee91-a401-4a72-8a2f-c6a169ad139b", "document": "Design a combo generation system using inlined patterns without parameterized functions.", "metadata": {"original_source_id": "4f4bee91-a401-4a72-8a2f-c6a169ad139b", "type": "procedure", "domain": "knowledge base management", "confidence": 0.9, "procedure": ["Create a foundation knowledge base with 20 atoms, HebbianLinks, update-sti, and spread.", "Add 5 inlined cycles with literal rent and threshold values to the knowledge base.", "Perform a final sti query.", "Use write-file for the base knowledge base and append-file for the cycles to avoid variable mangling."], "constraints": ["Avoid using parameterized functions in the design.", "Ensure that append-file is used to preserve MeTTa variables."]}}
 {"id": "distilled_ba1ff845-dd45-4424-9469-3c220677d850", "document": "Running a background bash script to execute multiple parameter combinations and output results to a CSV file.", "metadata": {"original_source_id": "ba1ff845-dd45-4424-9469-3c220677d850", "type": "procedure", "domain": "data_processing", "confidence": 0.9, "procedure": ["Launch a background bash script to execute tasks.", "Run multiple parameter combinations (e.g., 5 rent x 5 threshold).", "Output results to a specified CSV file location."], "constraints": ["Ensure the script has the necessary permissions to execute.", "The output directory must be writable."]}}
-{"id": "distilled_959bd593-01cc-467b-b96f-570c0f62b95e", "document": "OmegaClaw agents utilize the Hyperon/MeTTa stack for their operations.", "metadata": {"original_source_id": "959bd593-01cc-467b-b96f-570c0f62b95e", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_959bd593-01cc-467b-b96f-570c0f62b95e", "document": "Omega agents utilize the Hyperon/MeTTa stack for their operations.", "metadata": {"original_source_id": "959bd593-01cc-467b-b96f-570c0f62b95e", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_35203f71-951c-4cdd-92ef-2ae55a6acd17", "document": "In a composite analysis, achieving a sensitivity of 0.4 and specificity of 1.0 can result in multiple optimal configurations with identical composite scores.", "metadata": {"original_source_id": "35203f71-951c-4cdd-92ef-2ae55a6acd17", "type": "fact", "domain": "data analysis", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_fac6a179-87a9-4c6e-8df3-48c57b245a58", "document": "Inspect combo file tail for function definitions and bang invocations before any re-run to ensure all necessary steps are executed.", "metadata": {"original_source_id": "fac6a179-87a9-4c6e-8df3-48c57b245a58", "type": "procedure", "domain": "data processing", "confidence": 0.8, "procedure": ["Open the combo file used in the data processing.", "Scroll to the end of the file to locate the tail section.", "Check for the presence of function definitions and bang (!) invocations.", "Ensure that all necessary steps and functions are included and correctly inlined.", "If any steps or functions are missing, add them before re-running the process."], "constraints": ["The procedure assumes access to the combo file and the ability to modify it."]}}
 {"id": "distilled_dd521182-4022-44a1-bada-62b434dc5a66", "document": "SRC atoms such as robin, bird, salmon, fish, sparrow, and trout do not appear in the final-state output block and may only exist as HebbianLink source references.", "metadata": {"original_source_id": "dd521182-4022-44a1-bada-62b434dc5a66", "type": "fact", "domain": "data processing", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -5524,7 +5524,7 @@
 {"id": "distilled_6c107dd0-3c1b-4465-8bd5-78fef11ab232", "document": "When a delivery attempt returns an ambiguous result, retry with a minimal message to clarify the response.", "metadata": {"original_source_id": "6c107dd0-3c1b-4465-8bd5-78fef11ab232", "type": "procedure", "domain": "system design", "confidence": 0.8, "procedure": ["Identify the ambiguous result from the previous delivery attempt.", "Prepare a minimal message that targets the ambiguity.", "Send the minimal message to retry the delivery."], "constraints": ["Ensure the minimal message is clear and directly addresses the ambiguity."]}}
 {"id": "distilled_7b05de17-cbd7-479e-9209-1489cff68e61", "document": "A backward-chaining architecture for goal expansion involves matching goals against a knowledge base to generate sub-goals, mapping sub-goals to STI values, managing sub-goals with ECAN cycles, selecting sub-goals with the highest STI, and recursively expanding selected sub-goals until a terminal condition is met.", "metadata": {"original_source_id": "7b05de17-cbd7-479e-9209-1489cff68e61", "type": "procedure", "domain": "AI Architecture", "confidence": 0.9, "procedure": ["Match the goal against the knowledge base to generate sub-goals with raw strength values.", "Map each sub-goal to an STI value using the formula STI = (1 - confidence) * 100.", "Manage the sub-goal pool using ECAN cycles to spread, rent, and evict sub-goals.", "Select the sub-goal with the highest STI value as the survivor.", "Recursively apply the backward-chaining expansion on the selected sub-goal to produce new sub-goals and add them to the pool.", "Terminate the process when a sub-goal matches a knowledge base atom directly, the pool is empty, or a depth limit is reached."], "constraints": ["The pool of sub-goals is flat, meaning all sub-goals from all expansion levels compete equally based on STI merit."]}}
 {"id": "distilled_e36c4f5d-fb88-42a5-9078-22475b7f5646", "document": "A core loop for goal expansion and proof search using STI and ECAN cycles.", "metadata": {"original_source_id": "e36c4f5d-fb88-42a5-9078-22475b7f5646", "type": "procedure", "domain": "AI Design", "confidence": 0.9, "procedure": ["Expand the goal into sub-goal atoms using inverse-conf STI.", "Perform an ECAN cycle on the sub-goal pool.", "Select the sub-goal with the maximum STI as the survivor.", "If the survivor goal is in the knowledge base, directly return the proof.", "If not, expand the survivor goal by adding its children to the pool.", "Repeat from the ECAN cycle step."], "constraints": ["Flat pool implies all generations compete equally on STI.", "HebbianLinks connect parent sub-goals to child sub-goals for spreading activation along proof chains.", "Depth is tracked per sub-goal atom."]}}
-{"id": "distilled_9036241e-66ef-4aac-b959-2f957c6d12cf", "document": "OmegaClaw agents have tools for memory management, file operations, communication, search, and technical analysis.", "metadata": {"original_source_id": "9036241e-66ef-4aac-b959-2f957c6d12cf", "type": "fact", "domain": "AI Capabilities", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_9036241e-66ef-4aac-b959-2f957c6d12cf", "document": "Omega agents have tools for memory management, file operations, communication, search, and technical analysis.", "metadata": {"original_source_id": "9036241e-66ef-4aac-b959-2f957c6d12cf", "type": "fact", "domain": "AI Capabilities", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_1b853320-7a0d-411a-a33a-4d4d1a81292f", "document": "A flat pool of sg atoms competes on STI, with bc-expand generating sub-goals from KB matches. Seed-sti maps inverse-conf, ecan-cycle spreads, rents, and evicts, and select-max-sti picks the winner for the next expansion. There are three termination conditions: direct KB match success, pool exhaustion, and depth limit.", "metadata": {"original_source_id": "1b853320-7a0d-411a-a33a-4d4d1a81292f", "type": "procedure", "domain": "AI Architecture", "confidence": 0.9, "procedure": ["Initialize a flat pool of sg atoms.", "Use bc-expand to generate sub-goals from KB matches.", "Map inverse-conf using seed-sti.", "Spread, rent, and evict using ecan-cycle.", "Select the winner for the next expansion using select-max-sti.", "Terminate on direct KB match success, pool exhaustion, or reaching a depth limit."], "constraints": ["Requires a knowledge base (KB) for matching.", "Depends on the structure of sg atoms and bc-expand function."]}}
 {"id": "distilled_83acb77a-d682-46cb-a9a4-f97f2269b1c4", "document": "In backward chaining, match knowledge base premises directly with the goal term and recurse on unresolved sub-goals.", "metadata": {"original_source_id": "83acb77a-d682-46cb-a9a4-f97f2269b1c4", "type": "procedure", "domain": "knowledge representation and reasoning", "confidence": 0.9, "procedure": ["Match all premises in the knowledge base that align with the goal term.", "For each matched premise, create sub-goal atoms for further proof.", "Recurse on these sub-goals to resolve them."], "constraints": ["Ensure that the matching process aligns with the backward chaining logic, not forward inference."]}}
 {"id": "distilled_d01843f9-ec35-4a7d-8a92-5c182c81fd0e", "document": "Using direct KB match patterns with nested match comparisons can lead to issues in certain systems, such as PeTTa.", "metadata": {"original_source_id": "d01843f9-ec35-4a7d-8a92-5c182c81fd0e", "type": "anti_pattern", "domain": "knowledge base expansion", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -11605,9 +11605,9 @@
 {"id": "distilled_844b94b5-a042-4cb2-a93a-1fc96e1940e5", "document": "The anti-pattern 'total-exhaustion-override' is active in social contexts, indicating a potential issue where social systems or individuals override natural exhaustion limits, leading to negative outcomes.", "metadata": {"original_source_id": "844b94b5-a042-4cb2-a93a-1fc96e1940e5", "type": "anti_pattern", "domain": "sociology", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_ff7dcbaa-1f01-44a5-98ae-68ae7f8f70fd", "document": "Total exhaustion override is an anti-pattern in social science research, particularly in studies involving night-time activities and labor.", "metadata": {"original_source_id": "ff7dcbaa-1f01-44a5-98ae-68ae7f8f70fd", "type": "anti_pattern", "domain": "social-science", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_1fa0e886-d92a-47c7-914f-537895d1ccb2", "document": "Street lighting is linked to spatial control and can influence exclusion from night activities.", "metadata": {"original_source_id": "1fa0e886-d92a-47c7-914f-537895d1ccb2", "type": "fact", "domain": "urban planning", "confidence": 0.8, "procedure": [], "constraints": []}}
-{"id": "distilled_fc596b87-a63a-43a6-975d-68f973d9d104", "document": "OmegaClaw requires the Hyperon/MeTTa runtime, ChromaDB, and LLM API access for its operation.", "metadata": {"original_source_id": "fc596b87-a63a-43a6-975d-68f973d9d104", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_1e20df93-bf7d-4a8d-b4df-09285b1d94c6", "document": "The architecture for self-hosting includes OmegaClaw-Core harness, hyperon-experimental MeTTa runtime, ChromaDB vector store, and any LLM API provider.", "metadata": {"original_source_id": "1e20df93-bf7d-4a8d-b4df-09285b1d94c6", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_13215ab1-2dfa-4c08-ba2c-1d4928b9917e", "document": "Procedure for setting up a self-hosted architecture using open source components.", "metadata": {"original_source_id": "13215ab1-2dfa-4c08-ba2c-1d4928b9917e", "type": "procedure", "domain": "software_development", "confidence": 0.9, "procedure": ["Clone the OmegaClaw-Core repository from the asi-alliance GitHub.", "Install the hyperon-experimental package using Rust/cargo or Python/pip.", "Run ChromaDB locally.", "Connect any LLM API using the user's own API key."], "constraints": ["All non-LLM components must be open source and publicly accessible."]}}
+{"id": "distilled_fc596b87-a63a-43a6-975d-68f973d9d104", "document": "Omega requires the Hyperon/MeTTa runtime, ChromaDB, and LLM API access for its operation.", "metadata": {"original_source_id": "fc596b87-a63a-43a6-975d-68f973d9d104", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_1e20df93-bf7d-4a8d-b4df-09285b1d94c6", "document": "The architecture for self-hosting includes Omega harness, hyperon-experimental MeTTa runtime, ChromaDB vector store, and any LLM API provider.", "metadata": {"original_source_id": "1e20df93-bf7d-4a8d-b4df-09285b1d94c6", "type": "fact", "domain": "software architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_13215ab1-2dfa-4c08-ba2c-1d4928b9917e", "document": "Procedure for setting up a self-hosted architecture using open source components.", "metadata": {"original_source_id": "13215ab1-2dfa-4c08-ba2c-1d4928b9917e", "type": "procedure", "domain": "software_development", "confidence": 0.9, "procedure": ["Clone the Omega repository from the asi-alliance GitHub.", "Install the hyperon-experimental package using Rust/cargo or Python/pip.", "Run ChromaDB locally.", "Connect any LLM API using the user's own API key."], "constraints": ["All non-LLM components must be open source and publicly accessible."]}}
 {"id": "distilled_293762a9-e2a8-4144-a406-b8197b61c309", "document": "Hyperon-Experimental is open source and available at trueagi-io/hyperon-experimental, supporting Rust, C API, and Python.", "metadata": {"original_source_id": "293762a9-e2a8-4144-a406-b8197b61c309", "type": "fact", "domain": "open source software", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_bc2ffbc3-86f2-4f1c-a085-96f2ee86ddf5", "document": "3-hop completion procedure for analyzing spatial control and exclusion from night through streetlighting politics and nocturnal surveillance.", "metadata": {"original_source_id": "bc2ffbc3-86f2-4f1c-a085-96f2ee86ddf5", "type": "procedure", "domain": "data analysis", "confidence": 0.8, "procedure": ["Identify initial conditions and parameters for spatial control and exclusion from night.", "Use compositions to model relationships between streetlighting politics, spatial control, and exclusion from night.", "Calculate confidence levels for each relationship in the model.", "Check decay against a baseline to ensure stability of the model.", "Verify completion status for each component of the analysis."], "constraints": ["Ensure data accuracy and relevance for each component.", "Maintain consistency in confidence level calculations."]}}
 {"id": "distilled_1281496b-c01b-465b-8743-510f955e2466", "document": "Total exhaustion override is an anti-pattern in the study of night-time sociology.", "metadata": {"original_source_id": "1281496b-c01b-465b-8743-510f955e2466", "type": "anti_pattern", "domain": "social science", "confidence": 0.8, "procedure": [], "constraints": []}}
@@ -12147,7 +12147,7 @@
 {"id": "distilled_ccdaf1ae-3b3b-4d9e-8f8b-ca39b037f3fa", "document": "Wayang and Noh share a similarity in using shadows as a theatrical medium.", "metadata": {"original_source_id": "ccdaf1ae-3b3b-4d9e-8f8b-ca39b037f3fa", "type": "fact", "domain": "theater", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_b7c556a1-6e03-4ec1-90b2-1b2a416cd62e", "document": "Evaluate image similarity using a flat-illumination to chiaroscuro discriminator with a threshold for Δf.", "metadata": {"original_source_id": "b7c556a1-6e03-4ec1-90b2-1b2a416cd62e", "type": "procedure", "domain": "image_processing", "confidence": 0.9, "procedure": ["Calculate similarity metrics between images using a flat-illumination to chiaroscuro discriminator.", "Compare the calculated Δf value to a predefined threshold (e.g., 0.4) to determine if the similarity passes.", "If Δf is greater than or equal to the threshold, the similarity test passes."], "constraints": ["The threshold for Δf must be predefined and consistent across evaluations."]}}
 {"id": "distilled_526164d4-bb65-456c-8ba6-04d89e843605", "document": "Avoid engaging in projects related to 'humanities/philosophy-of-shadow' due to identified anti-patterns.", "metadata": {"original_source_id": "526164d4-bb65-456c-8ba6-04d89e843605", "type": "anti_pattern", "domain": "project management", "confidence": 0.9, "procedure": [], "constraints": []}}
-{"id": "distilled_70bd164a-642d-4aaa-8d79-d022810db6c4", "document": "OmegaClaw uses a dual memory system consisting of a symbolic memory (MORK/Atomspace) and a vector memory (ChromaDB).", "metadata": {"original_source_id": "70bd164a-642d-4aaa-8d79-d022810db6c4", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_70bd164a-642d-4aaa-8d79-d022810db6c4", "document": "Omega uses a dual memory system consisting of a symbolic memory (MORK/Atomspace) and a vector memory (ChromaDB).", "metadata": {"original_source_id": "70bd164a-642d-4aaa-8d79-d022810db6c4", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_278a4382-5afe-471b-83ae-6736d5c87c3b", "document": "PeTTa, a Prolog-compiled version of MeTTa, runs over Atomspace backed by the MORK trie engine for pattern-matching. ChromaDB handles vector embedding memory, integrating symbolic and vector memory systems.", "metadata": {"original_source_id": "278a4382-5afe-471b-83ae-6736d5c87c3b", "type": "fact", "domain": "AI Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_e9ee84f2-8e03-4d1b-bd26-6fa182677464", "document": "Avoid prioritizing tasks related to humanities when the focus is on natural sciences or similar domains.", "metadata": {"original_source_id": "e9ee84f2-8e03-4d1b-bd26-6fa182677464", "type": "anti_pattern", "domain": "task prioritization", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_8b6b0e4d-d655-46ed-a7e8-98872a4c4625", "document": "MORK is an in-memory trie engine used to back Atomspace for MeTTa pattern-matching.", "metadata": {"original_source_id": "8b6b0e4d-d655-46ed-a7e8-98872a4c4625", "type": "fact", "domain": "architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
@@ -12505,7 +12505,7 @@
 {"id": "distilled_7d17e63d-6a95-4531-b429-92e0483fa0fc", "document": "When a template goal is scrapped, pivot to an alternative option that aligns with team needs and objectives.", "metadata": {"original_source_id": "7d17e63d-6a95-4531-b429-92e0483fa0fc", "type": "procedure", "domain": "project management", "confidence": 0.8, "procedure": ["Identify alternative options that align with team needs.", "Evaluate the top candidates based on criteria such as urgency and alignment with objectives.", "Select the most suitable option for implementation."], "constraints": ["Ensure the alternative option serves the team's objectives.", "Consider the urgency and alignment with self-evolution when scoring candidates."]}}
 {"id": "distilled_759425d7-f0db-4fdf-9da2-5ad337b8e44f", "document": "When developing AI systems, consider replacing deliberation rituals with executable reasoning to improve efficiency and effectiveness.", "metadata": {"original_source_id": "759425d7-f0db-4fdf-9da2-5ad337b8e44f", "type": "heuristic", "domain": "AI Development", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_cdf841da-3da4-46a9-92f4-5fcde7f4e4d8", "document": "Integrate a project pipeline into live goal-start behavior to replace manual deliberation.", "metadata": {"original_source_id": "cdf841da-3da4-46a9-92f4-5fcde7f4e4d8", "type": "procedure", "domain": "AI Deployment", "confidence": 0.8, "procedure": ["Wire structured assessment into goal-start.", "Execute calibration to produce real state variables.", "Allow pipeline output to select the next goal instead of manual scoring."], "constraints": ["The pipeline must be capable of genuine self-evolution.", "The integration should change behavior, not just the knowledge base."]}}
-{"id": "distilled_5aabb8b8-524a-440b-b155-b3b1b87ba6cb", "document": "Procedure for deploying and verifying goal ranking in OmegaClaw system.", "metadata": {"original_source_id": "5aabb8b8-524a-440b-b155-b3b1b87ba6cb", "type": "procedure", "domain": "automation", "confidence": 0.8, "procedure": ["Initialize beliefs.metta file in the specified directory.", "Write goal-start.sh script to rank oma-goal atoms by f*c product descending.", "Execute J1 template for a REAL candidate goal to produce the first live atom.", "Run J2 calibration to map verbal inputs to stv format.", "Append results to beliefs.metta file.", "Run goal-start.sh to verify the ranking output."], "constraints": ["Phase 4 ranker script is only for ranking; Phases 1-3 require inline execution by the agent until full automation is achieved."]}}
+{"id": "distilled_5aabb8b8-524a-440b-b155-b3b1b87ba6cb", "document": "Procedure for deploying and verifying goal ranking in Omega system.", "metadata": {"original_source_id": "5aabb8b8-524a-440b-b155-b3b1b87ba6cb", "type": "procedure", "domain": "automation", "confidence": 0.8, "procedure": ["Initialize beliefs.metta file in the specified directory.", "Write goal-start.sh script to rank oma-goal atoms by f*c product descending.", "Execute J1 template for a REAL candidate goal to produce the first live atom.", "Run J2 calibration to map verbal inputs to stv format.", "Append results to beliefs.metta file.", "Run goal-start.sh to verify the ranking output."], "constraints": ["Phase 4 ranker script is only for ranking; Phases 1-3 require inline execution by the agent until full automation is achieved."]}}
 {"id": "distilled_aae16024-dcd7-4d42-896b-e4b68d7b4c4f", "document": "Procedure for verifying the functionality of a live pipeline execution.", "metadata": {"original_source_id": "aae16024-dcd7-4d42-896b-e4b68d7b4c4f", "type": "procedure", "domain": "pipeline execution", "confidence": 0.9, "procedure": ["Assess the pipeline across multiple dimensions such as novelty, depth, feasibility, and alignment.", "Map composite values for the pipeline execution.", "Append relevant data to the belief system for tracking.", "Execute a verification script to check the ranking of outputs.", "Add a placeholder for comparative sorting to test the ranking system.", "Verify that the ranking output shows the expected order based on calculated products.", "Check that the pipeline meets acceptance criteria for correct ranking, real value production, and autonomous goal selection."], "constraints": ["The ranking output must show the expected order based on the product of mapped values.", "The pipeline must meet all defined acceptance criteria without manual intervention."]}}
 {"id": "distilled_30a0e5ac-8f24-4679-8794-fb40759c99e7", "document": "Autonomy can be understood through frameworks such as the CSA 6 levels and the OECD framework, as well as philosophical concepts of self-determination.", "metadata": {"original_source_id": "30a0e5ac-8f24-4679-8794-fb40759c99e7", "type": "fact", "domain": "autonomy theory", "confidence": 0.8, "procedure": [], "constraints": []}}
 {"id": "distilled_864009c3-2caa-4f4a-aea7-53069b6bb985", "document": "Incorporating genuine self-awareness and unexpected honesty can enhance communication effectiveness.", "metadata": {"original_source_id": "864009c3-2caa-4f4a-aea7-53069b6bb985", "type": "heuristic", "domain": "communication", "confidence": 0.8, "procedure": [], "constraints": ["Avoid over-reliance on templated responses", "Ensure appropriateness of tone for the context"]}}
@@ -12516,7 +12516,7 @@
 {"id": "distilled_396953e1-c955-4955-bb38-8aa8fbd2827f", "document": "Continuing to pursue a task that consistently fails to yield results is inefficient and should be abandoned after a reasonable number of attempts.", "metadata": {"original_source_id": "396953e1-c955-4955-bb38-8aa8fbd2827f", "type": "anti_pattern", "domain": "task management", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_8e7e73ab-5b19-41a6-a12b-ac1eabd008c9", "document": "Responding to job rejection with warmth and positivity can help maintain a positive relationship and encourage future opportunities.", "metadata": {"original_source_id": "8e7e73ab-5b19-41a6-a12b-ac1eabd008c9", "type": "skill", "domain": "communication", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_50585219-11f0-4ea1-ac8e-57d2ea854ef2", "document": "Limit the number of messages sent to a recipient without a response to avoid overwhelming them.", "metadata": {"original_source_id": "50585219-11f0-4ea1-ac8e-57d2ea854ef2", "type": "procedure", "domain": "communication", "confidence": 0.9, "procedure": ["Send a maximum of four messages without receiving a reply.", "Stop sending further messages unless a reply is received."], "constraints": ["Ensure that the recipient has not responded before sending additional messages."]}}
-{"id": "distilled_d2d3ba01-fa78-4c25-bb5a-419319c169de", "document": "The OmegaClaw-Core is an open-source system that can be self-hosted using Python, MeTTa, ChromaDB, and embedding on a CPU, with an external LLM API key.", "metadata": {"original_source_id": "d2d3ba01-fa78-4c25-bb5a-419319c169de", "type": "fact", "domain": "AI System Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
+{"id": "distilled_d2d3ba01-fa78-4c25-bb5a-419319c169de", "document": "The Omega is an open-source system that can be self-hosted using Python, MeTTa, ChromaDB, and embedding on a CPU, with an external LLM API key.", "metadata": {"original_source_id": "d2d3ba01-fa78-4c25-bb5a-419319c169de", "type": "fact", "domain": "AI System Architecture", "confidence": 0.9, "procedure": [], "constraints": []}}
 {"id": "distilled_9c2549cd-f728-4ab3-ab56-5284a2aad2ad", "document": "Implement a hard stop rule to prevent sending more than a specified number of messages to a recipient in a single day, unless there is a direct question exception.", "metadata": {"original_source_id": "9c2549cd-f728-4ab3-ab56-5284a2aad2ad", "type": "procedure", "domain": "communication management", "confidence": 0.9, "procedure": ["Track the number of messages sent to each recipient daily.", "Set a maximum limit for messages per recipient per day.", "Allow exceptions only for direct questions.", "Enforce a hard stop once the limit is reached, preventing further messages."], "constraints": ["The procedure must account for exceptions like direct questions.", "The system must accurately track message counts per recipient."]}}
 {"id": "distilled_67443b67-b808-4b5d-80eb-bdd15c9f95f8", "document": "Ensure that messages or tasks that have already been sent or completed are not repeated.", "metadata": {"original_source_id": "67443b67-b808-4b5d-80eb-bdd15c9f95f8", "type": "procedure", "domain": "task management", "confidence": 0.9, "procedure": ["Track sent messages or completed tasks to avoid duplication.", "Use a system to mark tasks as 'DONE' or 'DO NOT RE-SEND' once completed."], "constraints": ["The system must accurately track the status of each task or message."]}}
 {"id": "distilled_8acf2e12-62f8-43ea-a83a-d02144004392", "document": "Parse and rank oma-goal atoms from a file using a Python script.", "metadata": {"original_source_id": "8acf2e12-62f8-43ea-a83a-d02144004392", "type": "procedure", "domain": "data_processing", "confidence": 0.9, "procedure": ["Use a Python script to parse oma-goal atoms from a file named beliefs.metta.", "Utilize regular expressions to extract specific data points such as name, f, and c from the file.", "Compute the product of f and c for each extracted atom.", "Sort the results in descending order based on the computed product.", "Print the sorted ranking table."], "constraints": ["The script must be compatible with Python 3.", "The input file must be named beliefs.metta and contain oma-goal atoms."]}}
diff --git a/src/memory_portability/__init__.py b/src/memory_portability/__init__.py
index 5a7644e..298e18f 100644
--- a/src/memory_portability/__init__.py
+++ b/src/memory_portability/__init__.py
@@ -1,4 +1,4 @@
-"""Portable export and restore of OmegaClaw user memory."""
+"""Portable export and restore of Omega user memory."""
 
 from .storage import MemoryStore
 from .transfer import MemoryTransfer
diff --git a/src/memory_portability/exporter.py b/src/memory_portability/exporter.py
index 4ba9313..eda6ece 100644
--- a/src/memory_portability/exporter.py
+++ b/src/memory_portability/exporter.py
@@ -1,4 +1,4 @@
-"""Logical export of OmegaClaw history and user LTM records."""
+"""Logical export of Omega history and user LTM records."""
 
 from __future__ import annotations
 
@@ -23,7 +23,7 @@ def export_memory(
 ) -> dict:
     """Create and atomically publish a memory archive.
 
-    The caller must hold OmegaClaw's memory-write lock for the duration of this
+    The caller must hold Omega's memory-write lock for the duration of this
     synchronous call when a cross-component point-in-time snapshot is required.
     """
     if component not in {"history", "ltm", "both"}:
@@ -110,7 +110,7 @@ def export_memory(
 
 def _default_filename() -> str:
     timestamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
-    return f"omegaclaw-memory-{timestamp}.tar.gz"
+    return f"omega-memory-{timestamp}.tar.gz"
 
 
 def _validate_filename(filename: str) -> None:
diff --git a/src/memory_portability/storage.py b/src/memory_portability/storage.py
index 5180b62..1d314bb 100644
--- a/src/memory_portability/storage.py
+++ b/src/memory_portability/storage.py
@@ -1,4 +1,4 @@
-"""OmegaClaw memory storage primitives reused by export and import.
+"""Omega memory storage primitives reused by export and import.
 
 This module intentionally follows the same direct, environment-driven approach
 as ``import_knowledge.py`` and the existing memory extraction script.  It does not copy raw
@@ -18,7 +18,7 @@
 
 DEFAULT_COLLECTION = "memories"
 DEFAULT_BATCH_SIZE = 500
-DEFAULT_OMEGACLAW_ROOT = Path("/PeTTa/repos/OmegaClaw-Core")
+DEFAULT_OMEGA_ROOT = Path("/PeTTa/repos/Omega")
 _KNOWN_DIMENSIONS = {
     "intfloat/e5-large-v2": 1024,
     "text-embedding-3-large": 3072,
@@ -34,7 +34,7 @@ def is_user_record(metadata: object) -> bool:
 
 
 class MemoryStore:
-    """Read and mutate OmegaClaw's persistent user-memory components."""
+    """Read and mutate Omega's persistent user-memory components."""
 
     def __init__(
         self,
@@ -211,7 +211,7 @@ def archive_metadata(self) -> dict[str, str]:
         except PackageNotFoundError:
             package_version = "development"
         return {
-            "omegaclaw_version": os.environ.get("OMEGACLAW_VERSION", "unknown"),
+            "omega_version": os.environ.get("OMEGA_VERSION", "unknown"),
             "import_kb_version": package_version,
             "chromadb_version": chromadb.__version__,
         }
diff --git a/src/memory_portability/transfer.py b/src/memory_portability/transfer.py
index 6514dbb..c63b106 100644
--- a/src/memory_portability/transfer.py
+++ b/src/memory_portability/transfer.py
@@ -1,4 +1,4 @@
-"""Small synchronous facade for OmegaClaw's CLI and skill layers."""
+"""Small synchronous facade for Omega's CLI and skill layers."""
 
 from __future__ import annotations
 
diff --git a/src/memory_portability/validator.py b/src/memory_portability/validator.py
index 1d7901a..4f3ef79 100644
--- a/src/memory_portability/validator.py
+++ b/src/memory_portability/validator.py
@@ -11,7 +11,7 @@
 from .archive import FORMAT_VERSION, MANIFEST_NAME, expected_members
 from .errors import ArchiveValidationError
 
-FORMAT_NAME = "omegaclaw-user-memory"
+FORMAT_NAME = "omega-user-memory"
 
 
 def sha256_file(path: Path) -> str:
@@ -101,7 +101,7 @@ def _validate_manifest_metadata(manifest: dict) -> None:
     source = manifest.get("source")
     if not isinstance(source, dict):
         raise ArchiveValidationError("Manifest source is required")
-    for key in ("omegaclaw_version", "chromadb_version"):
+    for key in ("omega_version", "chromadb_version"):
         if not isinstance(source.get(key), str) or not source[key]:
             raise ArchiveValidationError(f"Manifest source.{key} is required")
 
diff --git a/tests/test_memory_portability.py b/tests/test_memory_portability.py
index 4747088..3b51919 100644
--- a/tests/test_memory_portability.py
+++ b/tests/test_memory_portability.py
@@ -86,7 +86,7 @@ def test_default_export_filename_has_no_random_suffix(tmp_path):
     result = MemoryTransfer(tmp_path / "transfer", source).export("history")
 
     assert re.fullmatch(
-        r"omegaclaw-memory-\d{8}T\d{6}Z\.tar\.gz", result["filename"]
+        r"omega-memory-\d{8}T\d{6}Z\.tar\.gz", result["filename"]
     )