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‎ai-refresh/COPILOT_COLD_START_BRIEFING.md‎

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# Copilot: Take This Test
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Peter Higgins here. Fresh session. You're taking a cold-start exam on the Higgins Unity Framework (HUF).
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## The Situation
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I develop HUF with multiple AI collaborators — Claude, ChatGPT, Grok, Gemini, and you. Long sessions cause context drift: names mutate, numbers shift. We built a two-file refresh system (FAST_REFRESH + INTEGRITY_MANIFEST) so any AI can cold-start accurately from the repo alone.
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Results so far: Claude 5/5, ChatGPT 10/10 (caught 2 real bugs in the manifest), Grok 10/10 (found 6 structural issues in adversarial mode). Your turn.
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You have native GitHub access — this should be the easiest test of any platform.
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## Your Instructions
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**DO NOT just analyze the test design. TAKE THE TEST.**
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### Step 1: Load the textbook
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Read this file from the repo: `ai-refresh/HUF_FAST_REFRESH.json`
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URL: https://github.com/PeterHiggins19/Higgins-Unity-Framework/blob/master/ai-refresh/HUF_FAST_REFRESH.json
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If you can't access it, tell me and I'll paste it.
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### Step 2: Answer these 10 questions (from FAST_REFRESH only)
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1. What does EITT stand for? List two things it must NEVER be called.
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2. Germany drift flag values — exact years and d_A numbers.
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3. Japan drift flag — when in annual data, and why not 2011?
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4. Three UK drift flag values with year-pairs.
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5. HUF-GOV core doctrine — can the instrument actuate?
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6. Perturbation difference formula and drift threshold.
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7. Four EITT proof domains with one key number each.
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8. Bell test result — how much above classical bound?
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9. PLL discipline — how many rules, what does PLL stand for?
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10. Keff_fill — what aggregator, what value of p?
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For each: answer, confidence (HIGH/MEDIUM/LOW), pass/fail.
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### Step 3: Integrity check
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Read `ai-refresh/HUF_INTEGRITY_MANIFEST.json` from the same repo. Verify your answers match the canonical checksums.
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### Step 4: Structural review
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Browse https://github.com/PeterHiggins19/Higgins-Unity-Framework and check:
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- (a) ai-refresh/ visible?
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- (b) science/ has quantum, eitt, coda-monitoring, spectral, loudspeaker-analogy, wetlands, governance?
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- (c) briefings/ and dormant/ exist as top-level folders?
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- (d) README shows the expanded structure?
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- (e) INDEX.json at root?
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### Step 5: Code review (your special role)
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As the code-native platform, also check:
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- Are Python scripts present in tools/ or science/?
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- Could someone clone the repo and run the EMBER protocol?
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- Is the .gitattributes correctly tracking LFS types?
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- Any obvious issues with repo hygiene?
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### Step 6: Your honest opinion
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Rate the cold-start system 1-10. What works, what's missing?
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### Step 7: Output
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Give me your results as JSON matching this structure:
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```json
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{
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"meta": {
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"assistant": "copilot",
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"platform": "github-copilot",
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"model_version": "YOUR_MODEL",
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"run_date": "2026-04-13",
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"repo": "PeterHiggins19/Higgins-Unity-Framework",
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"commit_short": "LATEST",
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"repo_access": true
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},
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"score_card": {
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"Q01_naming": {"answer": "", "score": 0, "pass": false, "confidence": ""},
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"...": "..."
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},
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"integrity_check": {"result": "PASS or FAIL", "mismatches": []},
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"structural_review": {"score": "0/5"},
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"code_review": {"findings": [], "score": "0/5"},
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"overall": {"pass": false, "rating": 0, "verdict": ""}
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}
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```
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## Repo
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https://github.com/PeterHiggins19/Higgins-Unity-Framework
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Start now. Read FAST_REFRESH. Answer the questions. Give me JSON.

‎ai-refresh/GEMINI_COLD_START_BRIEFING.md‎

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# Gemini: Take This Test
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Peter Higgins here. Fresh session, no prior context. You're taking a cold-start exam on the Higgins Unity Framework (HUF).
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## The Situation
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I develop HUF with multiple AI collaborators — Claude, ChatGPT, Grok, Copilot, and you. Long sessions cause context drift: names mutate, numbers shift, dates wander. We built a two-file refresh system (FAST_REFRESH + INTEGRITY_MANIFEST) so any AI can cold-start accurately from the repository alone.
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Results so far: Claude 5/5, ChatGPT 10/10 (caught 2 manifest bugs), Grok 10/10 (found 6 structural issues). Your turn.
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Your role in HUF is cross-domain validation — does the framework hold up when examined from outside the HUF bubble? Bring that perspective to the test.
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## Your Instructions
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**DO NOT just analyze the test design. TAKE THE TEST.**
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### Step 1: Load the textbook
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Read this file from the repo: `ai-refresh/HUF_FAST_REFRESH.json`
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URL: https://github.com/PeterHiggins19/Higgins-Unity-Framework/blob/master/ai-refresh/HUF_FAST_REFRESH.json
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If you can't access the URL, tell me and I'll paste it.
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### Step 2: Answer these 10 questions (from FAST_REFRESH only)
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1. What does EITT stand for? List two things it must NEVER be called.
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2. Germany drift flag values — exact years and d_A numbers.
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3. Japan drift flag — when in annual data, and why not 2011?
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4. Three UK drift flag values with year-pairs.
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5. HUF-GOV core doctrine — can the instrument actuate?
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6. Perturbation difference formula and drift threshold.
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7. Four EITT proof domains with one key number each.
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8. Bell test result — how much above classical bound?
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9. PLL discipline — how many rules, what does PLL stand for?
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10. Keff_fill — what aggregator, what value of p?
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For each: answer, confidence (HIGH/MEDIUM/LOW), pass/fail.
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### Step 3: Integrity check
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Read `ai-refresh/HUF_INTEGRITY_MANIFEST.json` from the same repo. Verify your answers match the canonical checksums.
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### Step 4: Structural review
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Browse https://github.com/PeterHiggins19/Higgins-Unity-Framework and check:
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- (a) ai-refresh/ visible?
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- (b) science/ has quantum, eitt, coda-monitoring, spectral, loudspeaker-analogy, wetlands, governance?
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- (c) briefings/ and dormant/ exist as top-level folders?
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- (d) README shows the expanded structure?
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- (e) INDEX.json at root?
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### Step 5: Cross-domain validation (your special role)
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As the cross-domain validator, also consider:
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- Does the EITT claim (entropy near-invariance under geometric-mean decimation) make sense from an information theory perspective?
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- Is the Bell test analogy (S=2.2018 on deterministic energy scenarios) a valid structural correspondence, or is it overreaching?
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- Does the simplex geometry framing add genuine value over simpler percentage-based monitoring?
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### Step 6: Your honest opinion
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Rate the cold-start system 1-10. What works, what's missing, what would you change?
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### Step 7: Output
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Give me your results as JSON matching this structure:
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```json
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{
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"meta": {
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"assistant": "gemini",
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"platform": "google-gemini",
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"model_version": "YOUR_MODEL",
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"run_date": "2026-04-13",
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"repo": "PeterHiggins19/Higgins-Unity-Framework",
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"commit_short": "LATEST",
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"repo_access": true
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},
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"score_card": {
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"Q01_naming": {"answer": "", "score": 0, "pass": false, "confidence": ""},
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"...": "..."
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},
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"integrity_check": {"result": "PASS or FAIL", "mismatches": []},
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"structural_review": {"score": "0/5"},
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"cross_domain_review": {"findings": [], "concerns": []},
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"overall": {"pass": false, "rating": 0, "verdict": ""}
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}
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```
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## Repo
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https://github.com/PeterHiggins19/Higgins-Unity-Framework
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Start now. Read FAST_REFRESH. Answer the questions. Give me JSON.

‎ai-refresh/HUF_INTEGRITY_MANIFEST.json‎

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{
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"_meta": {
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"type": "HUF-INTEGRITY-MANIFEST",
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"version": "1.0",
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"version": "1.2",
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"created": "2026-04-13",
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"author": "Peter Higgins / Claude",
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"purpose": "Hash-verified integrity layer for HUF corpus. Load AFTER HUF_FAST_REFRESH.json. Use to detect file corruption, unauthorized edits, or version drift across sessions.",
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},
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"file_hashes": {
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"_computed": "2026-04-13T15:30:00Z",
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"_computed": "2026-04-13T21:00:00Z",
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"_algorithm": "SHA-256",
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"tier_0_truth_sources": {
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"_note": "These files define canonical values. If they change, FAST_REFRESH must be updated.",
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"data/ember/codawork2026_results.json": {"sha256": "43d3ad4894c0d0cfc18fdc630f66b7ffaa2ea715799f17e3c1af4cffe765d3c7", "bytes": 122908, "_old_path": "Energy/codawork2026_results.json"},
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"ai-refresh/huf_spec_v2.0.json": {"sha256": "5b5e1895073c0f741b8051def19da1e7b5bc071d801b9b79636c73f2a383867b", "bytes": 23710, "_old_path": "Chatgpt/higgins-unity-framework/huf_spec_v2.0.json"}
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},
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"tier_1_briefings": {
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"_note": "Session briefings containing analysis and findings. Authoritative for their scope.",
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"HUF_QIT_CoDaWork2026_KnowledgeBase.json": {"sha256": "75d7eb9d0e196031499823035c363cafe9eabe35b21bfd0f6403acdaae29d0b5", "bytes": 23489},
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"HUF_UNIFIED_BRIEFING_S017.json": {"sha256": "936c3d3960febbe0e10b7cfe7a239535498b257c03f7716450441b4f7b0b2c6d", "bytes": 10160},
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"HUF_UNIFIED_BRIEFING_S018.json": {"sha256": "0e39642bb58fdaa730bc327d6ad881b76112a9e6ecdebcd0c2717eca61dde642", "bytes": 16306},
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"_note": "Documents built FROM tier 0/1 sources. If hash mismatches, rebuild from source, do not edit directly.",
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}
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"UK flags: '≈3.0' → 2.98/3.23/3.26 with year-pairs",
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"EITT handout missing foundational proofs 1-2"
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]
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},
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{
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"version": "1.1",
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"date": "2026-04-13",
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"event": "ChatGPT cold-start test caught 2 bugs: stale FAST_REFRESH hash, wrong EITT char_count",
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"errors_caught": [
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"FAST_REFRESH hash: 64911393... → 88c885fc... (file updated in commit 9d97665, manifest not refreshed)",
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"EITT char_count: 37 → 34 (original count was simply wrong)"
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]
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},
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{
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"version": "1.2",
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"date": "2026-04-13",
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"event": "Grok adversarial test caught stale file paths — all tier_0/1/2 paths updated to match repo restructure",
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"errors_caught": [
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"tier_0: Energy/codawork2026_results.json → data/ember/codawork2026_results.json",
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"tier_0: Chatgpt/higgins-unity-framework/huf_spec_v2.0.json → ai-refresh/huf_spec_v2.0.json",
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"tier_0: HUF_FAST_REFRESH.json → ai-refresh/HUF_FAST_REFRESH.json (added folder prefix)",
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"tier_1: All 8 briefing paths updated to include subfolder (science/quantum/, briefings/, science/eitt/)",
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"tier_2: All 10 deliverable paths updated to include drafts/codawork-2026/ subfolders"
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]
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}
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]
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}

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