Autoresearch

Turn Claude Code, OpenCode, or OpenAI Codex into a relentless improvement engine.

Based on Karpathy's autoresearch — constraint + mechanical metric + autonomous iteration = compounding gains.

"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, and OpenAI Codex for the core skill, bundled runtime, installation, and verification surface. Hook guardrails are Claude Code-only.

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.

How It Works · Commands · Quick Start · Guides · FAQ

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     PLAN             LOOP            DEBUG             FIX             SECURE            SHIP
 ┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐
 │   Goal   │     │  Modify  │     │   Find   │     │   Fix    │     │  STRIDE  │     │  Stage   │
 │  Metric  │────▶│  Verify  │────▶│   Bugs   │────▶│  Errors  │────▶│  OWASP   │────▶│  Deploy  │
 │  Scope   │     │Keep/Drop │     │  Trace   │     │  Repair  │     │ Red Team │     │ Release  │
 └──────────┘     └──────────┘     └──────────┘     └──────────┘     └──────────┘     └──────────┘
 /autoresearch:   /autoresearch    /autoresearch:   /autoresearch:   /autoresearch:   /autoresearch:
   plan                              debug            fix              security         ship

 ┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐
 │  Probe   │     │ Scenario │     │ Predict  │     │  Reason  │
 │ Require- │     │   Edge   │     │ 5-Expert │     │  Debate  │
 │  ments   │     │  Cases   │     │  Swarm   │     │ Converge │
 └──────────┘     └──────────┘     └──────────┘     └──────────┘
 /autoresearch:   /autoresearch:   /autoresearch:   /autoresearch:
   probe            scenario         predict          reason

 ┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐
 │  Learn   │     │ Improve  │     │   Eval   │     │ Baseline │
 │   Docs   │     │ Research │     │ Analyze  │     │   Diff   │
 │   Gen    │     │   PRDs   │     │ Results  │     │ Verdict  │
 └──────────┘     └──────────┘     └──────────┘     └──────────┘
 /autoresearch:   /autoresearch:   /autoresearch:   /autoresearch:
   learn            improve          evals            regression

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Why This Exists

Karpathy's autoresearch demonstrated that a 630-line Python script could autonomously improve ML models overnight — 100 experiments per night — by following simple principles: one metric, constrained scope, fast verification, automatic rollback, git as memory.

Claude Autoresearch generalizes these principles to ANY domain. Not just ML — code, content, marketing, sales, HR, DevOps, or anything with a number you can measure.