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Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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
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.
Generate explanatory diagrams and infographics that visually communicate concepts. Iterates autonomously until images are logically correct, text is clean, and the concept explanation is clear. Uses Nano Banana (Gemini 2.5 Flash Image).
Run a full coherence analysis of the knowledge base using the Brain Dependency Graph engine. Identifies stale notes, lifecycle transitions, structural issues, and optionally productive tensions.
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| LBS Graph | resources/local-brain-search/data/brain_graph.pkl | ✓ | NetworkX graph | |
| Enrichments | resources/brain-graph/data/graph_enrichments.json | ✓ | ✓ | Node/edge enrichments |
| Reports | resources/brain-graph/reports/ | ✓ | Generated reports |
run_brain_graph.sh bootstrap)cd $PROJECT_ROOT/resources/brain-graph
../local-brain-search/venv/bin/python cli.py status
If not bootstrapped, run bootstrap first:
../local-brain-search/venv/bin/python cli.py bootstrap
Default (7-day lookback, lifecycle included, no tensions):
../local-brain-search/venv/bin/python cli.py coherence
With options:
# Include tension detection (slower)
../local-brain-search/venv/bin/python cli.py coherence --tensions
# Custom lookback period
../local-brain-search/venv/bin/python cli.py coherence --days 14
# JSON output
../local-brain-search/venv/bin/python cli.py coherence --json
Read the generated report and present key findings to the user:
Report is saved to: resources/brain-graph/reports/coherence-report-YYYY-MM-DD.md
Present a concise summary with: