The project's README from github.com/uditgoenka/autoresearch. As one markdown file: README.md.
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
/autoresearchand 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
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
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.
v2.1.0 is a major architecture rebuild. The monolithic SKILL.md (813 lines, ~100K tokens per invocation) is replaced with a thin 41-line routing file and 12 self-contained command files (94–120 lines each, ~5–8K tokens per invocation). That is a 95% token reduction with the same capability surface.
LOOP (N iterations or until done):
1. Review current state + git history + results log
2. Pick the next change (based on what worked, what failed, what's untried)
3. Make ONE focused change
4. Git commit (before verification)
5. Run mechanical verification (tests, benchmarks, scores)
6. If improved → keep. If worse → git revert. If crashed → fix or skip.
7. Log the result
8. Repeat until N iterations complete or goal is met.
Every improvement stacks. Every failure auto-reverts. Progress is logged in TSV format.
Before looping, Claude performs a one-time setup:
| # | Rule |
|---|---|
| 1 | Bounded by default — every command has a default iteration count; unlimited is opt-in via Iterations: unlimited |
| 2 | Read before write — understand full context before modifying |
| 3 | One change per iteration — atomic changes; if it breaks, you know why |
| 4 | Mechanical verification only — no subjective "looks good"; use metrics |
| 5 | Automatic rollback — failed changes revert instantly |
| 6 | Simplicity wins — equal results + less code = keep |
| 7 | Git is memory — experiments committed with experiment: prefix; agent reads git log + git diff before each iteration |
| 8 | When stuck, think harder — re-read, combine near-misses, try radical changes |
Hooks are defense-in-depth guardrails, not a security sandbox. Claude Code ships the hook surface; OpenCode and Codex ship the core skill/runtime/install surface without hook parity.
| Hook | What it does | Event |
|---|---|---|
| scout-block | Blocks node_modules/, .git/, pycache/, etc. from filling your context | PreToolUse |
| privacy-block | Blocks .env, SSH keys, credentials from being read in sessions | PreToolUse |
| dangerous-cmd-block | Blocks force-push, rm -rf, git reset --hard |
PreToolUse |
| iteration-context | Injects recent TSV iteration data after context compaction | UserPromptSubmit |
| subagent-context | Gives subagents awareness of active loop state | SubagentStart |
| dev-rules-reminder | Re-injects plan path and code standards after compaction | UserPromptSubmit |
| simplify-gate | Warns at 400 LOC, blocks at 800 LOC before shipping | UserPromptSubmit |
| session-init | Sets up project context at session start | SessionStart |
| stop-notify | Terminal notification + optional webhook on session end | SessionEnd |
All hooks are on by default. Disable individually only for troubleshooting:
# Disable a specific hook
export AR_DISABLE_SCOUT_BLOCK=1
export AR_DISABLE_PRIVACY_BLOCK=1
export AR_DISABLE_DANGEROUS_CMD_BLOCK=1
# ... etc for each hook name
Optional webhook for session completion notifications:
export AR_NOTIFY_WEBHOOK=https://hooks.slack.com/services/...
Customize blocked directories with a .ckignore file (gitignore syntax) at your project root.
See guide/hooks.md for full reference.
Release preparation and contributor verification live in scripts/release.md.
| Command | What it does | Default Iterations |
|---|---|---|
/autoresearch |
Classic: Core iterate loop: modify → verify → keep/discard · Orchestrator: free-form goal → auto-select pipeline → loop until predicate met | 25 / goal-bounded |
/autoresearch:plan |
Convert goal into validated config | one-shot |
/autoresearch:debug |
Hunt bugs via hypothesis iteration | 15 |
/autoresearch:fix |
Crush errors one-by-one to zero | 20 |
/autoresearch:security |
STRIDE + OWASP audit with red-team | 15 |
/autoresearch:ship |
Ship through 8 phases | linear |
/autoresearch:scenario |
Generate edge cases across 12 dimensions | 20 |
/autoresearch:predict |
5 expert personas debate | one-shot |
/autoresearch:learn |
Scout → generate docs → validate → fix | 10 |
/autoresearch:reason |
Adversarial debate with blind judges | 8 |
/autoresearch:probe |
8 personas interrogate requirements | 15 |
/autoresearch:improve |
Research ICP, discover improvements, generate PRDs | 15 |
/autoresearch:evals |
Analyze iteration results: trends, plateaus | one-shot |
/autoresearch:regression |
Stability gate: baseline vs candidate, verdict STABLE/UNSTABLE | one-shot |
Universal flags: Iterations: N, Iterations: unlimited, --evals, --evals-interval N, --chain <targets>, --<subcommand> shorthand.
All commands use interactive setup when invoked without arguments. Just type the command — the agent asks for what it needs with smart defaults based on your codebase.
OpenCode users: Commands use underscore naming (
/autoresearch_debug,/autoresearch_fix, etc.). All 14 commands available.Codex users: Invoke via
$autoresearchmention syntax. Subcommands are keywords:$autoresearch debug,$autoresearch plan, etc.
| I want to... | Use |
|---|---|
| Give a plain-language goal, let it self-orchestrate | /autoresearch <goal> (bare, no Metric/Verify) |
| Improve test coverage / reduce bundle size / any metric | /autoresearch |
| Run bounded iterations | Add Iterations: N to any command |
| Don't know what metric to use | /autoresearch:plan |
| Run a security audit | /autoresearch:security |
| Ship a PR / deployment / release | /autoresearch:ship |
| Optimize without breaking existing tests | Add Guard: npm test |
| Hunt all bugs in a codebase | /autoresearch:debug |
| Fix all errors (tests, types, lint) | /autoresearch:fix |
| Debug then auto-fix | /autoresearch:debug --fix |
| Check if something is ready to ship | /autoresearch:ship --checklist-only |
| Explore edge cases for a feature | /autoresearch:scenario |
| Generate test scenarios | /autoresearch:scenario --format test-scenarios |
| Get expert opinions before starting | /autoresearch:predict |
| Analyze from multiple angles then debug | /autoresearch:predict --chain debug |
| Generate docs for a new codebase | /autoresearch:learn --mode init |
| Update existing docs after changes | /autoresearch:learn --mode update |
| Debate an architecture decision | /autoresearch:reason --domain software |
| Surface hidden constraints before starting | /autoresearch:probe |
| Pre-flight a fuzzy goal then loop | /autoresearch:probe --chain plan,autoresearch |
| Discover what to build next for your ICP | /autoresearch:improve |
| Research competitors and generate PRDs | /autoresearch:improve --depth deep |
| Probe requirements then research improvements | /autoresearch:probe --improve |
| Analyze trends and plateaus across past runs | /autoresearch:evals |
| Check if a run has stalled | /autoresearch:evals --file *-results.tsv |
| Verify a change won't regress before pushing | /autoresearch:regression |
| Gate a PR: predict, fix, re-gate, then ship | /autoresearch:regression --predict --fix --ship |
Option A — npx install (recommended):
npx skills add uditgoenka/autoresearch
All 14 commands are available after restarting Claude Code.
Option B — Plugin install:
/plugin marketplace add uditgoenka/autoresearch
/plugin install autoresearch@autoresearch
Note: Start a new Claude Code session after installing. Reference files aren't resolvable in the same session where installation happened — this is a Claude Code platform limitation.
Updating (no reinstall needed):
/plugin update autoresearch
Run /reload-plugins to activate. No need to uninstall or re-clone.
Option C — Manual copy:
git clone https://github.com/uditgoenka/autoresearch.git
# Copy skill + subcommands to your project
cp -r autoresearch/.claude/skills/autoresearch .claude/skills/autoresearch
cp -r autoresearch/.claude/commands/autoresearch .claude/commands/autoresearch
cp autoresearch/.claude/commands/autoresearch.md .claude/commands/autoresearch.md
Or install globally:
cp -r autoresearch/.claude/skills/autoresearch ~/.claude/skills/autoresearch
cp -r autoresearch/.claude/commands/autoresearch ~/.claude/commands/autoresearch
cp autoresearch/.claude/commands/autoresearch.md ~/.claude/commands/autoresearch.md
Option D — Guided installer:
git clone https://github.com/uditgoenka/autoresearch.git
cd autoresearch
./scripts/install.sh --claude --global
Option A — Guided installer (recommended):
git clone https://github.com/uditgoenka/autoresearch.git
cd autoresearch
./scripts/install.sh --opencode --global
Option B — Manual copy:
git clone https://github.com/uditgoenka/autoresearch.git
cp -r autoresearch/.opencode/skills/autoresearch .opencode/skills/autoresearch
cp autoresearch/.opencode/commands/autoresearch*.md .opencode/commands/
Or globally:
cp -r autoresearch/.opencode/skills/autoresearch ~/.config/opencode/skills/autoresearch
cp autoresearch/.opencode/commands/autoresearch*.md ~/.config/opencode/commands/
All 14 commands available as
/autoresearch_debug,/autoresearch_fix,/autoresearch_improve, etc.
Option A — Guided installer (recommended):
git clone https://github.com/uditgoenka/autoresearch.git
cd autoresearch
./scripts/install.sh --codex --global
Option B — Manual copy:
git clone https://github.com/uditgoenka/autoresearch.git
cp -r autoresearch/.agents/skills/autoresearch ~/.codex/skills/autoresearch
Invoke via
$autoresearchmention syntax. Subcommands are keywords:$autoresearch plan,$autoresearch debug,$autoresearch evals, etc. The installed Codex package includes the bundled orchestrator and regression helpers underplugins/autoresearch/skills/autoresearch/and.agents/skills/autoresearch/.
/autoresearch
Goal: Increase test coverage from 72% to 90%
Scope: src/**/*.test.ts, src/**/*.ts
Metric: coverage % (higher is better)
Verify: npm test -- --coverage | grep "All files"
Iterations: 25
Claude reads all files, establishes a baseline, and starts iterating — one change at a time. Keeps improvements, auto-reverts failures, logs everything. Stops after N iterations or when you interrupt.
The hardest part isn't the loop — it's defining Scope, Metric, and Verify correctly. /autoresearch:plan converts your plain-language goal into a validated, ready-to-execute configuration.
/autoresearch:plan
Goal: Make the API respond faster
Walks through 5 steps: capture goal → define scope → define metric → define direction → validate verify command (dry-run). Every gate is mechanical — scope must resolve to files, metric must output a number, verify must pass a dry-run. Emits a handoff.json for chaining.
Scientific method meets autoresearch loop. Doesn't stop at one bug — iteratively hunts ALL bugs using falsifiable hypotheses, evidence-based investigation, and 7 investigation techniques.
/autoresearch:debug
Scope: src/api/**/*.ts
Symptom: API returns 500 on POST /users
Iterations: 15
How it works: Gather symptoms → Recon → Hypothesize (specific, testable) → Test (one experiment per iteration) → Classify (confirmed/disproven/inconclusive) → Log → Repeat.
Every finding requires code evidence (file:line + reproduction steps). Every disproven hypothesis is logged — equally valuable.
| Flag | Purpose |
|---|---|
--fix |
After hunting, auto-switch to /autoresearch:fix |
--scope <glob> |
Limit investigation scope |
--symptom "<text>" |
Pre-fill symptom |
--severity <level> |
Minimum severity to report |
Takes a broken state and iteratively repairs it until everything passes. ONE fix per iteration. Atomic, committed, verified, auto-reverted on failure.
/autoresearch:fix
Iterations: 20
Auto-detects what's broken (tests, types, lint, build) → Prioritizes (blockers first) → Fixes ONE thing → Commits → Verifies error count decreased → Guard check → Keep/Revert → Repeat. Stops automatically when error count hits zero.
| Flag | Purpose |
|---|---|
--target <command> |
Explicit verify command |
--guard <command> |
Safety command that must always pass |
--category <type> |
Only fix specific type (test, type, lint, build) |
--from-debug |
Read findings from latest debug session |
Chain them: /autoresearch:debug → /autoresearch:fix --from-debug
Read-only security audit using STRIDE threat modeling, OWASP Top 10 sweeps, and red-team adversarial analysis with 4 hostile personas.
/autoresearch:security
Iterations: 15
Codebase recon → asset inventory → trust boundaries → STRIDE threat model → attack surface map → autonomous testing loop → structured report. Every finding requires code evidence (file:line + attack scenario).
| Flag | Purpose |
|---|---|
--diff |
Only audit files changed since last audit |
--fix |
Auto-fix confirmed Critical/High findings |
--fail-on <severity> |
Exit non-zero for CI/CD gating |
Output: Creates security/{date}-{slug}/ with 7 structured report files.
Ship anything through 8 phases: Identify → Inventory → Checklist → Prepare → Dry-run → Ship → Verify → Log.
/autoresearch:ship --auto
Auto-detects what you're shipping (code PR, deployment, blog post, email campaign, sales deck, research paper, design assets) and generates domain-specific che