# Refine

> 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.

- Skill: `primeintellect-ai/refine` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add primeintellect-ai/refine`
- Raw SKILL.md: https://api.skillmd.com/api/skills/primeintellect-ai/refine/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: primeintellect-ai (https://skillmd.com/u/primeintellect-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/primeintellect-ai/refine

---


# 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.