By name: detect-tensions description: Detect productive contradictions between notes - high semantic similarity with opposing conclusions that represent synthesis opportunities allowed-tools: [Bash, Read] user-invocable: true automation: gated
Detect Productive Tensions
Scans the knowledge base for productive contradictions: note pairs with high semantic similarity but opposing conclusions. These tension zones are where the most valuable articles and frameworks emerge.
State Dependencies
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| Enrichments | resources/brain-graph/data/graph_enrichments.json |
✓ | ✓ | Tension records saved |
| FAISS Index | resources/local-brain-search/data/brain.faiss |
✓ | Similarity search | |
| Metadata | resources/local-brain-search/data/brain_metadata.pkl |
✓ | Note content |
Process
Step 1: Run tension detection
Default thresholds (similarity > 0.75, divergence > 0.3):
cd "$(git rev-parse --show-toplevel)"/resources/brain-graph
../local-brain-search/venv/bin/python cli.py tensions
Broader search (more results, lower quality):
../local-brain-search/venv/bin/python cli.py tensions --similarity 0.70 --divergence 0.2
Step 2: Present synthesis opportunities
For each tension, explain:
- What the two notes assert
- Why they contradict
- What synthesis opportunity exists (article topic, framework potential)
Step 3: Track existing tensions
../local-brain-search/venv/bin/python cli.py status --json
Check tension_count for total tracked tensions.
Key Principle
Tensions are features, not bugs. The system NEVER auto-resolves tensions. It surfaces them as the most productive intellectual territory in the vault.