| name | compute-lifecycle |
| description | Compute lifecycle scores for all insight and framework notes - detect which notes are crystallizing or becoming generative |
| allowed-tools | ["Bash","Read"] |
| user-invocable | true |
| automation | gated |
Compute Lifecycle Scores
Computes lifecycle scores (0.0 reflective -> 1.0 generative) for all insight and framework notes based on behavioral signals: citation frequency, generative ratio, cross-domain reach, and temporal acceleration.
State Dependencies
| Source | Location | Read | Write | Description |
|---|
| Enrichments | resources/brain-graph/data/graph_enrichments.json | ✓ | ✓ | Updated lifecycle scores |
| LBS Graph | resources/local-brain-search/data/brain_graph.pkl | ✓ | | NetworkX graph |
| Brain files | Brain/**/*.md | ✓ | | File mtimes for temporal signals |
Process
Step 1: Run lifecycle computation
cd $PROJECT_ROOT/resources/brain-graph
../local-brain-search/venv/bin/python cli.py lifecycle
For JSON output:
../local-brain-search/venv/bin/python cli.py lifecycle --json
Step 2: Present transitions
Focus on notes that crossed phase boundaries:
- Reflective -> Crystallizing: Note is starting to generate its own connections
- Crystallizing -> Generative: Note has become a driver of new insights
For promotable notes, suggest:
- "Consider promoting to framework status"
- "This note drives connections across N domains"
Lifecycle Phases
| Score Range | Phase | Meaning |
|---|
| 0.0 - 0.3 | Reflective | Tracks sources, sources win on conflict |
| 0.3 - 0.6 | Crystallizing | Generating own connections, authority contested |
| 0.6 - 1.0 | Generative | Drives downstream notes, this note wins on conflict |
