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Compound

Skill toverux/grimoire/skills/compound

πŸ€– Curated agent skills for AI agents β€” one coherent engineering loop that compounds: grill β†’ spec β†’ implement β†’ review β†’ commit β†’ learn. Adopt it or fork it!

Install
npx -y skills add toverux/grimoire --skill compound

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 27 days oldThe repository was created 27 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Capture this session's durable learnings and route each to the right knowledge store, every write user-gated. Use at loop end when /commit's opening scan finds candidates, when /diagnosing-bugs closes out a fix, or when the user wants to capture, remember, or write down a learning, convention, gotcha, decision, or preference.

SKILL.md

4.5 KB, as published. Nobody here has run it

Harvest what this session learned so future sessions inherit it. Only knowledge that compounds gets written; every write is approved by the user first.

1. Scan the session

Sweep the whole session for candidates: corrections the user made and preferences they stated, conventions that emerged, durable decisions settled or reversed, gotchas and root causes uncovered, approaches that failed and why, domain terms coined or clarified ("we call this X, not Y"), and workflow friction a procedure could remove.

2. Apply the quality bar

For each candidate, two questions: would this change a future agent's behavior in a different session, and is it non-obvious and stable? Any "no" β†’ discard.

This bar is the defence against the eager-auto-memory failure mode: session-specific trivia β€” in-flight task state, one-off values, things any agent would infer anyway β€” must die here.

If nothing clears the bar, say so in one line and stop.

3. Route each survivor

  1. Project AGENTS.md β€” durable shared preferences and conventions, cheap enough to always load. Domain terms go in its glossary section; when the glossary outgrows AGENTS.md, propose graduating it to a CONCEPTS.md file.
  2. docs/adr/ (opt-in store) β€” durable decisions: a project-shaping choice settled among live alternatives β€” where AGENTS.md holds preferences and docs/solutions/ holds problem-shaped learnings. One record per decision, per adr-format.md. Reversing a standing decision routes as a pair β€” a new ADR plus the status flip on the superseded record.
  3. docs/solutions/ (opt-in store) β€” problem-shaped learnings: root cause, gotcha, what didn't work. One small file per solved problem, per solutions-format.md. Expensive knowledge, loaded on demand.
  4. Project-local rules β€” path-scoped project conventions, when the project uses rules files.
  5. Skills β€” project-specific procedures β†’ the project's skills directory (.claude/skills/ on Claude Code, or the harness's equivalent); generic workflow improvements β†’ the user's personal skills collection, if configured.
  6. User-global memory file (~/.claude/CLAUDE.md on Claude Code, ~/.codex/AGENTS.md on Codex CLI, or the harness's equivalent) β€” personal-only preferences, and the staging area to trial a candidate durable preference before graduating it to a shared file.

The two opt-in stores take writes only where the repo enables them: docs/agents/cantrips-loop.md lists the enabled stores; when that doc is absent, both are off. A survivor aimed at a disabled store is presented with that store's own remedy β€” enable it through /setup-cantrips-loop β€” or dropped; a durable decision belongs in docs/adr/, so rerouting one into AGENTS.md, which holds preferences, is no substitute.

4. Gate every write

Present the survivors as one list: for each, the proposed destination and a one-line rationale. The user answers per candidate β€” approve, redirect (different destination or wording), or kill. A write happens only on an approval.

5. Write the approved ones

  • Before editing AGENTS.md, a rules file, or a skill: load the /writing-great-skills skill (../writing-great-skills/SKILL.md) and hold the edit to it.
  • Before writing to docs/adr/: read adr-format.md and hold to it, and search the store for the record a reversal supersedes β€” the pair only lands when its other half is found.
  • Before writing to docs/solutions/: read solutions-format.md, then search existing docs (frontmatter area, tags, symptoms) for one covering the same problem β€” fold fresh context into an existing doc rather than writing a near-duplicate.

Done when every approved candidate is written to its store. The writes join the working tree: /commit's flow picks them up when it invoked this scan; on an ad-hoc run, close with a flow pointer (read flow-pointers.md for the format): /commit (user-invoked) β€” it lands these writes with the rest of the diff.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.