一键导入
coherence-sweep
Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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).
| name | coherence-sweep |
| description | Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report |
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: