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 OpenCode'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. ## 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 ...