Iterating towards optimal agentic performance.
- detect/signals.py: pure extractors over digests (retry storm, repeated errors, budget overrun vs corpus p90, abandoned, clean pass, recovery) - detect/cluster.py: deterministic clustering into candidate Patterns with evidence (sessions/repos/flavors/cost impact) + cross-flavor flagging - detect/__main__.py: python -m session_memory.detect, ranked report (cross-flavor first) + --json; persists candidates to Tier 2 patterns table - core/store.py: list_digests + save_patterns - tests for signals, cluster, detect entrypoint Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| docs | ||
| session_memory | ||
| tests | ||
| workplans | ||
| .custodian-brief.md | ||
| .gitignore | ||
| AGENTS.md | ||
| INTENT.md | ||
| LICENSE | ||
| README.md | ||
| SCOPE.md | ||
Iterating towards optimal agentic performance.