creanlab TAMA Community Summarizer
Aggregates and summarizes research pool data for community intelligence.
When to Use
After receiving packs in research-pool/incoming/ or when querying community data.
Procedure
1. Collect Packs
Read all files in research-pool/incoming/.
2. Aggregate
Count by:
- Failure family (which families are most common?)
- Violated invariant (which rules are broken most?)
- Repair operator (which fixes are most reusable?)
- Stack tags (which stacks have most issues?)
3. Identify Patterns
- Most common failure families → community anti-patterns
- Most effective repair operators → community best practices
- Transferability hotspots → universally applicable lessons
4. Generate Summary
Save to research-pool/summaries/SUMMARY-YYYYMMDD.json:
{
"summary_date": "2026-03-18",
"total_packs": 5,
"total_genomes": 42,
"top_families": [
{ "family": "verification-skipped-before-done", "count": 12 },
{ "family": "silent-fallback-introduced", "count": 9 }
],
"top_repair_operators": [
{ "operator": "add-e2e-verification-step", "count": 8 }
],
"transfer_recommendations": [...]
}
5. For Dashboard
If integrated with frontend, provide community data via /api/community endpoint.