// Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report
| 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 "$(git rev-parse --show-toplevel)"/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:
Compute lifecycle scores for all insight and framework notes - detect which notes are crystallizing or becoming generative
Autonomous research pipeline - discover, extract, and integrate cutting-edge insights into knowledge base
Detect productive contradictions between notes - high semantic similarity with opposing conclusions that represent synthesis opportunities
Autonomous perception layer - scans KB for new notes matching domain watch configs, checks gap resonance with the Thinking Registry, probes external signals via web search, and auto-activates HIGH/MEDIUM signals into the Thinking Registry for the incubation loop.
Extract insights from external documents (research papers, books, articles). Spawns document-insight-extractor subagent. Requires session name.
Extract the transcript from a YouTube video by URL or video ID. Use when the user shares a YouTube link and wants the transcript, captions, or text content of the video. Falls back automatically if the requested language isn't available.