autoresearch

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# Autoresearch

**Turn [Claude Code](https://docs.anthropic.com/en/docs/claude-code), [OpenCode](https://opencode.ai), [OpenAI Codex](https://developers.openai.com/codex), [pi](https://github.com/earendil-works/pi-coding-agent), or Muse into a relentless improvement engine.**

Based on [Karpathy's autoresearch](https://github.com/karpathy/autoresearch) — constraint + mechanical metric + autonomous iteration = compounding gains.

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*"Set the GOAL → The agent runs the LOOP → You wake up to results"*

*You don't need AGI. You need a goal, a metric, and a loop that never quits.*

**Supports Claude Code, OpenCode, OpenAI Codex, pi, and Muse for the core skill, bundled runtime, installation, and verification surface. Hook guardrails ship for Claude Code (native hooks) and pi (extension events).**

> **Fork-and-flush:** metric loops escape plateaus the way [Cai et al. (arXiv:2610.07447)](https://arxiv.org/abs/2610.07447) do. At 33% and 66% of the budget, or after 5 iterations with no `keep`, the loop forks fresh-context branches from the best commit so far, runs each briefly, and keeps the winner. Half the branches pick their own ideas (randomness); the other half each get a distinct experiment from a stateless Advisor that reads the results log ([Zhang et al., arXiv:2610.07625](https://arxiv.org/abs/2610.07625)); `Guided: R` sets the split. The orchestrator answers a plateau with `FORK` before it gives up. See [guide/autoresearch.md](guide/autoresearch.md#getting-unstuck-fork-and-flush).

> **v2.2.0 — Autonomous Orchestrator:** Type a plain-language goal to `/autoresearch` and it classifies your goal, derives a Success predicate, confirms it once, then loops across subcommands until done. No manual chaining required. `Metric:`/`Verify:` invocations run the classic loop unchanged. See [guide/autoresearch-orchestrator.md](guide/autoresearch-orchestrator.md).

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