Add knowledge management: LightRAG-backed GraphRAG knowledge base

[osick]

Persist what a run learns (files, AST entities, dependency graph, user
stories) into a queryable knowledge base instead of only writing a JSON
report. GraphRAG was chosen over an LLM-wiki or vanilla RAG because a
codebase is a graph: multi-hop and global questions need entity/relation
retrieval, and the exact dependency graph from static analysis can seed the
knowledge graph without spending LLM tokens. LightRAG (MIT) was selected
for its incremental inserts, custom-KG import, pluggable Anthropic/OpenAI/
Ollama adapters and storage back-ends (NetworkX/Neo4j/Postgres/Memgraph,
nano-vectordb/pgvector/Qdrant/Milvus/FAISS, JSON/Postgres/Redis/Mongo).

• New workflow node knowledge_base (opt-in: archaeo --knowledge-base,
  knowledge_base.enabled in config) with deterministic indexing and an
  optional LLM entity-extraction pass (--kb-extract)
• New MCP server knowledge-base (kb_query, kb_retrieve, kb_context,
  kb_graph, kb_stats, kb_add_documents, kb_export_wiki), registered in the
  config and the in-process MCP client
• New CLI archaeo-kb (query, retrieve, context, graph, stats, add, wiki)
• Obsidian-compatible Markdown wiki export as the human-facing projection
• Offline mode (byte tokenizer, hashing embeddings) used by the new tests
• AST entities now carry file_path so members link to their file
• Docs: docs/KNOWLEDGE_MANAGEMENT.md decision record, README, quickstart,
  MCP usage, changelog; example under examples/knowledge_base; v0.4.0

Co-Authored-By: Claude Fable 5.1 noreply@anthropic.com
Claude-Session: https://claude.ai/code/session_011hwnef5pyjkdpQ6deZJYDD