Open spans at the memory hot paths (all no-op when tracing is off):
- add / flush (service.memorize), extract + persist.markdown (user pipeline).
- search: everos.memory.search retriever + a uniform recall / rank
decomposition across keyword / vector / hybrid / agentic (manager, agentic
modules, cross-encoder callbacks); query-embedding tokens land on recall.
- recall quality: top_score / hit on the search span, plus recall_top_score /
recall_hit pushed to Langfuse scores via the bounded-queue sink (method
tagged; off the request path).
- OME: everos.ome.<strategy> agent span + everos.reflect.consolidate
generation; a W3C traceparent captured at enqueue is threaded through the
APScheduler job and re-attached in the Runner, so strategies fanned out
from a request nest under that request's trace.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
md-first memory extraction framework for AI agents.
Markdown is the single source of truth; SQLite holds state and LanceDB
provides the rebuildable vector + BM25 + scalar index. The codebase follows
a single-direction DDD layering (entrypoints -> service -> memory -> infra,
with component / core / config cross-cutting) enforced by import-linter.
Engineering surface:
- Coding conventions in .claude/rules/ (path-scoped) and workflows in
.claude/skills/ (/commit, /new-branch, /pr).
- GitHub Actions CI runs make lint + test + integration; pre-commit mirrors
the gates locally (ruff, hygiene hooks, gitlint commit-msg).
- Commit messages follow Conventional Commits, enforced by gitlint.
- make lint also enforces datetime two-zone discipline and OpenAPI drift.
zhanghui
Elliot Chen
Elliot Chen