| 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 |
Propagate Framework/Note Change
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.
State Dependencies
| 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 |
Process
Step 1: Run propagation
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
Step 2: Present affected notes
Show the user which notes are flagged for review, sorted by staleness score.
For each affected note, explain:
- Why it's flagged (which upstream change, through what edge type)
- Suggested action: review, update, or mark as OK
Step 3: Offer to inspect specific notes
If the user wants details on any affected note:
../local-brain-search/venv/bin/python cli.py inspect "<NOTE_NAME>"
When to Use
- After substantially editing a framework or key insight note
- When the user says they've updated their thinking on a topic
- After ingesting new source material that contradicts existing notes
