evolisted

# Evo Apply natural-language lessons to evolution overlays. **Overlay model:** agent/skill files are never modified after vendoring (only a one-time marker injection points to the overlay). Lessons accumulate in `.ievo/evolution/<scope>/<name>.md` and are read live at every dispatch. This is fundamentally different from "patch the file inline" — see the rationale at the bottom. ## Inputs - **Required:** lesson text (free-form natural language) - **Optional:** explicit target ("apply this to spec-writer agent" / "this is project-wide") If the lesson is too vague (e.g. "be better"), ask for clarification first. ## On Claude Code with the iEvo plugin If the `evolution` sub-agent is available, delegate via Task tool with `subagent_type: "evolution"`. Pass the lesson verbatim. Otherwise execute the steps below directly. ## Step 0: Auto-evolution candidate intake (optional) Run this step **only** when reviewing the auto-evolution backlog — e.g. the user is responding to the SessionStart nudge ("N evolution candidates pending — review?") from `/ievo:evo-auto-enable`, or explicitly asks to review captured candidates. For an ordinary single-lesson capture, skip straight to Step 1. When `.ievo/evo-auto.flag` exists, corrections captured in earlier sessions live in per-session accumulator files under `.ievo/evolution-candidates/`. List them with the accumulator (path: `<plugin>/scripts/evolution_candidates.mjs`): ``` node <plugin>/scripts/evolution_candidates.mjs list ``` Fo