--- name: refine description: Trigger continual harness refinement from the Python REPL. Use when you notice a repeated failure, reusable tactic, delegation role, or behavior policy that should be persisted as a harness entry. Returns immediately; refinement runs when the current turn ends. --- # Refine Refinement analyzes the conversation trajectory and applies small, evidence-backed updates to the continual harness (prompts, memories, skills, subagent specs). The implementation lives in the host (the same one behind the user's `/refine` command); this skill is the kernel-side interface to it. Call it directly from the Python REPL: ```python await refine.status() await refine.run() await refine.run("create a memory about always checking git status before committing") await refine.run("promote the error-handling pattern to a global skill", global_=True) ``` ## API - `await refine.status()` — current refine state as a dict: `pending` (whether a requested refine is already queued for this turn) and `in_flight` (whether a refine is currently planning or applying). - `await refine.run(instructions=None, global_=False)` — schedule refinement. Returns `{"scheduled": True}` immediately, or `{"scheduled": False, "reason": ...}` when refinement cannot start. Optional `instructions` focus the refinement on a specific observation. Set `global_=True` to target the global harness store (cross-session); omit for local (session-scoped) refinement. ## Rules - Refinement never runs mid-cell. A scheduled refinement runs when the current turn ends; the harness applies changes and rebuilds the system prompt, then resumes you automatically. Continue working normally after calling it. - One request per turn is enough; calling `run` again before the turn ends only updates the instructions. - Use refinement after observing a repeated failure, a reusable tactic, a repeated delegation role, or a behavior policy worth persisting. Do not rewrite the whole harness when a focused memory, skill, prompt note, or subagent spec is enough.