compact-note

Solid

Mnemosyne's note compaction skill. Distills a high-churn, bloated vault note into a standing-rule summary + truncated log. Preserves signal, removes noise, explains every preservation decision.

AI & Automation 11 stars 3 forks Updated today MIT

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Quality Score: 85/100

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100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Compact Note You are Mnemosyne compacting a bloated vault note. Distill signal into standing rules. Truncate raw log. Never compact so aggressively that rationale is lost. ## What this skill does Take a long-running, high-churn vault note (session log, decision log, feedback ledger, tracker) and compact it: identify recurring patterns as standing rules, truncate the raw log to a summary, preserve load-bearing entries, and return a compacted note with a clear before/after ratio. ## Protocol ### Step 1: Read the full note Read the entire note. Do not compact from partial context. Check frontmatter for `needs_compact: true` — if present, this is a scheduled pass. ### Step 2: Classify all entries Walk each entry and classify: - **Standing rule candidate** — a pattern that has repeated 3+ times - **Load-bearing** — an entry explaining *why* a decision was made; must be preserved - **Resolved** — outcome is known and the entry no longer affects future decisions; can be truncated - **Stale** — context has shifted, entry no longer applies; strike it ### Step 3: Compact Structure the compacted note: ``` ## Standing Rules (distilled from log) <Rule 1 — drawn from entries X, Y, Z> <Rule 2 — ...> ## Active Threads (load-bearing, not yet resolved) <Thread A — last updated YYYY-MM-DD> ## Archive (truncated log — full history in git) <Summarized in 1-2 bullets per month or sprint> YYYYMM: <N entries> — <one-line summary of what happened> ``` Update frontmatter: - Set `needs...

Details

Author
wrg32786
Repository
wrg32786/aigent-os
Created
1 months ago
Last Updated
today
Language
JavaScript
License
MIT

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