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Periodic trust sweep of persistent memory and durable knowledge notes - re-verifies environment-dependent claims against the live environment, stamps last_verified + confidence, and proposes archiving drifted entries
$ npx -y skills add huytieu/COG-second-brain --skill memory-hygiene --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/memory-hygieneContext preview
The summary Claude sees to decide when to auto-load this skill.
Periodic trust sweep of persistent memory and durable knowledge notes - re-verifies environment-dependent claims against the live environment, stamps last_verified + confidence, and proposes archiving drifted entries
name: memory-hygiene description: Periodic trust sweep of persistent memory and durable knowledge notes - re-verifies environment-dependent claims against the live environment, stamps last_verified + confidence, and proposes archiving drifted entries roles: [all] integrations: []
Prevent the **stale-but-confident** failure mode: a memory or knowledge note that was correct when written ("the webhook lives at X", "the board ID is Y") silently drifts after the environment changes, yet still ranks high at recall and gets acted on.
The system move (adapted from "From Model Scaling to System Scaling: Scaling the Harness in Agentic AI", Gu, UC Berkeley, arXiv:2605.26112): **make trust a runtime decision, not a property of the stored item**. Re-verify against the live environment, and keep per-entry `last_verified` and `confidence` as first-class fields so future recalls can weigh trust.
Sweep two stores:
1. **Agent memory** — wherever your agent keeps persistent memory files (e.g. Claude Code's auto-memory directory). Sweep every entry except the index itself. 2. **Durable knowledge notes** — `05-knowledge/**` files whose claims reference the environment (paths, URLs, IDs, tool names).
A partial sweep ("just the reference entries") is fine when asked.
For each entry, split its claims into two buckets:
| Bucket | Examples | Action | |---|---|---| | **Environment-dependent** | file/dir paths, repo names, branch names, channel IDs, board IDs, URLs, API endpoints, cron/routine IDs, CLI names, version numbers, "X lives at Y" | Verify against the live environment | | **Preference / judgment** | tone rules, formatting rules, "never do X", people facts, strategy context | No environment check possible; verify only for internal contradiction with newer entries |
Never spend more than ~1 minute per entry. This is hygiene, not an investigation. **Unverifiable ≠ drifted.**
After checking an entry, update its frontmatter `metadata:` block in place (do not touch body text unless fixing a verified-wrong fact):
metadata: type: reference last_verified: 2026-07-10 confidence: high # high = verified now | medium = unverifiable cheaply | low = partially drifted
Scan-until-done over the entry list with a per-entry budget guard (~1 min). The deterministic verifier is the environment itself (`test -e`, `curl`, `gh`) — never the agent's own recollection of whether something "should" still exist. Human escalation: all deletions/archives.
Write one report per sweep to `01-daily/YYYY-MM-DD-memory-hygiene.md`, structured around four evolution questions:
1. **What persists?** — counts by type (user/feedback/project/reference). 2. **What updated?** — entries whose body was corrected, with old → new. 3. **What is measured?** — scorecard: `verified / unverifiable / drifted / propose-archive` counts, plus deltas vs the previous sweep report (the drift *trend* is the longitudinal signal one-shot checks miss). 4. **What is auditable?** — every change in this sweep is a line in this report; for stores Git does not track, the report IS the audit trail.
End the report with a **Propose archive** section (explicit list, one line of evidence each) and a **Waiting on you** line if anything needs a decision.
Cognition + Obsidian + Git — A self-evolving second brain powered by AI agents, markdown files, and version control. No database, no vendor lock-in — just .md files that think.
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