Memory To Skill

You manage MemSearch's procedural memory: skills distilled from the work you repeat — a third layer beside the daily journals (episodic) and PROJECT.md / USER.md (semantic). State once that this is MemSearch skill distillation, not the host agent's built-in skills system.

Stages: 0 memory journals → 1 candidate (.memsearch/skill-candidates/, a git-tracked store that keeps evolving) → 2 installed (an agent skill dir). Candidates are never installed automatically; installing is always a human step. User requests may stop at candidate creation/review, or continue to installation in the same turn after explicit approval; match the requested stage.

The plugins.<platform>.memory_to_skill.* config key prefix and the install-path notes are platform-specific — see your platform reference file:

• Claude Code → references/claude-code.md
• Codex → references/codex.md
• OpenClaw → references/openclaw.md
• OpenCode → references/opencode.md
• DeepSeek Harness → references/dsh.md

Intent routing

• "make/turn this into a skill", "from what we just did" → A. Capture now.
• "what skills / review candidates / install X" → B. Review & install.
• "mine my history / find recurring workflows" → C. Distill from history.
• "enable / configure / how eager" → D. Configure.
• Unclear or empty → run B's list; if empty, offer A or C.

A. Capture what you just did (0→1→2)

You already have the context, so draft the skill yourself — do not call the background distiller for this. Write a SKILL.md body (markdown, no frontmatter): imperative numbered steps for the recurring task, concrete commands and paths, no secrets, self-contained.

Be exact — do not guess. You have the live session for what you just did, so use the real commands, paths, and output, not approximations. If a detail is uncertain, verify it (re-read the relevant files or the transcript) or keep that step general — a wrong command is worse than a vague one. Then persist it as a candidate:

printf '%s' "## <title>\n\n1. ...\n2. ..." | memsearch skills add \
  --name "<short-slug>" \
  --description "<what it does AND when it should trigger — lead with the verbs a user types>" \
  --body-file -

add handles slugging, standard frontmatter, meta.json, and the git commit — no LLM is involved. Then show it to the user; install it only if the user asked for that or explicitly approves (see B). Finally, check whether background distillation is on; if not, offer to enable it (so recurring workflows get captured automatically going forward) — do not force it.

B. Review & install candidates (1→2)

memsearch skills status          # pending candidate versions needing install
memsearch skills list            # add -j for sources / installed paths
git -C .memsearch/skill-candidates log --oneline -5 2>/dev/null || true

skills status compares each candidate's current SKILL.md content hash with the hash recorded by the last skills install. It does not inspect live agent skill directories. A pending installed skill means the candidate source evolved after the last deliberate install; reinstall only after reviewing the candidate.

Before recommending or installing, skim the candidate's body: if a step looks uncertain or loosely summarized, re-check it against the source (open the transcript if needed) or flag it to the user and let them decide — installing copies the candidate as-is, so this is the last chance to catch a wrong step. When showing candidates, mention the store's recent git history when it helps explain whether a candidate is new, evolved, removed, or re-created.

Treat installation as an interactive checkpoint. Show the candidate, apply any requested tweaks before installing, and confirm the install destination with the user. Resolve install targets from config first: if paths is a non-empty list, present those paths as the proposed destinations and pass each entry as a --path after confirmation. If it is empty, ask the user where to install; do not silently fall back to a default path.

memsearch config get plugins.<platform>.memory_to_skill.paths 2>/dev/null || echo "[]"
memsearch skills install <name> --path <configured-or-user-approved-path>

Replace <platform> with your platform key prefix (see the reference file). After installation, remind the user to start a fresh agent session or reopen the conversation so the newly installed skill is loaded.

If the list is empty, background distillation is likely off or has not run. Offer the user a choice: capture from recent work now (A), distill from history (C), or enable the background pass (D).