القائمة
Propagate staleness from a changed note through the Brain Dependency Graph - shows which downstream notes need review
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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.
| name | propagate-change |
| description | Propagate staleness from a changed note through the Brain Dependency Graph - shows which downstream notes need review |
| argument-hint | <note name> |
| allowed-tools | ["Bash","Read"] |
| user-invocable | true |
| automation | gated |
When a note is substantially edited, this skill computes which downstream notes may be stale and need review. Uses the Brain Dependency Graph's staleness propagation engine with edge-type decay, distance decay, and hub dampening.
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| Enrichments | resources/brain-graph/data/graph_enrichments.json | ✓ | ✓ | Updated staleness scores |
| LBS Graph | resources/local-brain-search/data/brain_graph.pkl | ✓ | NetworkX graph |
cd $PROJECT_ROOT/resources/brain-graph
../local-brain-search/venv/bin/python cli.py propagate "<NOTE_NAME>"
Optional: specify change magnitude (0.0-1.0) for partial changes:
../local-brain-search/venv/bin/python cli.py propagate "<NOTE_NAME>" --magnitude 0.5
Show the user which notes are flagged for review, sorted by staleness score.
For each affected note, explain:
If the user wants details on any affected note:
../local-brain-search/venv/bin/python cli.py inspect "<NOTE_NAME>"