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Rebuild the Local Brain Search FAISS index to reflect vault changes
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | refresh-index |
| description | Rebuild the Local Brain Search FAISS index to reflect vault changes |
| automation | autonomous |
| schedule | 0 5 * * * |
| allowed-tools | Bash |
Rebuild the Local Brain Search vector index to ensure semantic search reflects current vault state.
The FAISS index is not auto-updated. This playbook rebuilds it so semantic search stays accurate.
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| Brain notes | Brain/**/*.md | ✓ | Source content to index | |
| Index script | resources/local-brain-search/run_index.sh | ✓ | Indexer | |
| FAISS index | resources/local-brain-search/brain_index/ | ✓ | Output index |
resources/local-brain-search/Check indexer exists:
test -f resources/local-brain-search/run_index.sh && echo "OK" || echo "MISSING"
If missing, abort.
resources/local-brain-search/run_index.sh
The indexer rebuilds the FAISS index and the connection graph in full on every
run, and writes a build manifest to data/manifest.json stamping the edge
formula (cosine_ip) and builder_version. After any change to the indexing
or edge logic (e.g. the semantic-edge similarity formula), pass --force to
make the full rebuild explicit and bump BUILDER_VERSION in memory_config.py
so the manifest records the new build:
resources/local-brain-search/run_index.sh --force
Confirm index works:
resources/local-brain-search/run_connections.sh --stats --json
Should return valid JSON with note count > 0.
The BDG enrichments depend on the LBS graph. After reindexing, re-classify nodes and edges:
resources/brain-graph/run_brain_graph.sh bootstrap --force
Verify:
resources/brain-graph/run_brain_graph.sh status
Should show enriched nodes matching the new index count.
resources/local-brain-search/data/resources/brain-graph/data/graph_enrichments.json| Error | Recovery |
|---|---|
| Script missing | Abort - check Local Brain Search installation |
| Index fails | Check Python env, disk space |
| Stats return 0 notes | Re-run indexer, check Brain path |
| BDG bootstrap fails | Non-critical - LBS index still works without BDG |
Autonomous AI crystallization - synthesizes converged thinking topics into ai-inferred notes in a dedicated folder. Never touches the human-curated permanent knowledge base and never changes a topic's status, so manual crystallization stays available to the user.
Analyze knowledge base structure and update the knowledge-base-analysis.md report
Discover non-obvious cross-domain connections through random sampling and pattern analysis
Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report
Compute lifecycle scores for all insight and framework notes - detect which notes are crystallizing or becoming generative
Create long-form articles from knowledge base insights. Use when writing articles, blog posts, Substack content, or synthesizing knowledge into publishable content. Includes tone of voice, structure templates, and knowledge base integration.