Autoresearch

---
name: autoresearch
description: Autonomous Goal-directed Iteration. Apply Karpathy's autoresearch principles to ANY task. Loops autonomously — modify, verify, keep/discard, repeat. Supports optional loop count via Claude Code's /loop command.
version: 1.0.4
---

# Claude Autoresearch — Autonomous Goal-directed Iteration

Inspired by [Karpathy's autoresearch](https://github.com/karpathy/autoresearch). Applies constraint-driven autonomous iteration to ANY work — not just ML research.

**Core idea:** You are an autonomous agent. Modify → Verify → Keep/Discard → Repeat.

## Subcommands

| Subcommand | Purpose |
|------------|---------|
| `/autoresearch` | Run the autonomous loop (default) |
| `/autoresearch:plan` | Interactive wizard to build Scope, Metric, Direction & Verify from a Goal |
| `/autoresearch:security` | Autonomous security audit: STRIDE threat model + OWASP Top 10 + red-team (4 adversarial personas) |

### /autoresearch:security — Autonomous Security Audit (v1.0.3)

Runs a comprehensive security audit using the autoresearch loop pattern. Generates a full STRIDE threat model, maps attack surfaces, then iteratively tests each vulnerability vector — logging findings with severity, OWASP category, and code evidence.

Load: `references/security-workflow.md` for full protocol.

**What it does:**

1. **Codebase Reconnaissance** — scans tech stack, dependencies, configs, API routes
2. **Asset Identification** — catalogs data stores, auth systems, external services, user inputs
3. **Trust Boundary Mapping** — browser↔server, public↔authenticated, user↔admin, CI/CD↔prod
4. **STRIDE Threat Model** — Spoofing, Tampering, Repudiation, Info Disclosure, DoS, Elevation of Privilege
5. **Attack Surface Map** — entry points, data flows, abuse paths
6. **Autonomous Loop** — iteratively tests each vector, validates with code evidence, logs findings
7. **Final Report** — severity-ranked findings with mitigations, coverage matrix, iteration log

**Key behaviors:**
- Follows red-team adversarial mindset (Security Adversary, Supply Chain, Insider Threat, Infra Attacker)
- Every finding requires **code evidence** (file:line + attack scenario) — no theoretical fluff
- Tracks OWASP Top 10 + STRIDE coverage, prints coverage summary every 5 iterations
- Composite metric: `(owasp_tested/10)*50 + (stride_tested/6)*30 + min(findings, 20)` — higher is better
- Creates `security/{YYMMDD}-{HHMM}-{audit-slug}/` folder with structured reports:
  `overview.md`, `threat-model.md`, `attack-surface-map.md`, `findings.md`, `owasp-coverage.md`, `dependency-audit.md`, `recommendations.md`, `security-audit-results.tsv`

**Flags:**

| Flag | Purpose |
|------|---------|
| `--diff` | Delta mode — only audit files changed since last audit |
| `--fix` | After audit, auto-fix confirmed Critical/High findings using autoresearch loop |
| `--fail-on {severity}` | Exit non-zero if findings meet threshold (for CI/CD gating) |

**Usage:**
```
# Unlimited — keep finding vulnerabilities until interrupted
/autoresearch:security

# Bounded — exactly 10 security sweep iterations
/loop 10 /autoresearch:security

# With focused scope
/autoresearch:security
Scope: src/api/**/*.ts, src/middleware/**/*.ts
Focus: authentication and authorization flows

# Delta mode — only audit changed files since last audit
/autoresearch:security --diff

# Auto-fix confirmed Critical/High findings after audit
/loop 15 /autoresearch:security --fix

# CI/CD gate — fail pipeline if any Critical findings
/loop 10 /autoresearch:security --fail-on critical

# Combined — delta audit + fix + gate
/loop 15 /autoresearch:security --diff --fix --fail-on critical
```

**Inspired by:**
- [Strix](https://github.com/usestrix/strix) — AI-powered security testing with proof-of-concept validation
- `/plan red-team` — adversarial review with hostile reviewer personas
- OWASP Top 10 (2021) — industry-standard vulnerability taxonomy
- STRIDE — Microsoft's threat modeling framework

### /autoresearch:plan — Goal → Configuration Wizard

Converts a plain-language goal into a validated, ready-to-execute autoresearch configuration.

Load: `references/plan-workflow.md` for full protocol.

**Quick summary:**

1. **Capture Goal** — ask what the user wants to improve (or accept inline text)
2. **Analyze Context** — scan codebase for tooling, test runners, build scripts
3. **Define Scope** — suggest file globs, validate they resolve to real files
4. **Define Metric** — suggest mechanical metrics, validate they output a number
5. **Define Direction** — higher or lower is better
6. **Define Verify** — construct the shell command, **dry-run it**, confirm it works
7. **Confirm & Launch** — present the complete config, offer to launch immediately

**Critical gates:**
- Metric MUST be mechanical (outputs a parseable number, not subjective)
- Verify command MUST pass a dry run on the current codebase before accepting
- Scope MUST resolve to ≥1 file

**Usage:**
```
/autoresearch:plan
Goal: Make the API respond faster

/autoresearch:plan Increase test coverage to 95%

/autoresearch:plan Reduce bundle size below 200KB
```

After the wizard completes, the user gets a ready-to-paste `/autoresearch` invocation — or can launch it directly.

## When to Activate

- User invokes `/autoresearch` or `/ug:autoresearch` → run the loop
- User invokes `/autoresearch:plan` → run the planning wizard
- User invokes `/autoresearch:security` → run the security audit
- User says "help me set up autoresearch", "plan an autoresearch run" → run the planning wizard
- User says "security audit", "threat model", "OWASP", "STRIDE", "find vulnerabilities", "red-team" → run the security audit
- User says "work autonomously", "iterate until done", "keep improving", "run overnight" → run the loop
- Any task requiring repeated iteration cycles with measurable outcomes → run the loop

## Optional: Controlled Loop Count

By default, autoresearch loops **forever** until manually interrupted. However, users can optionally specify a **loop count** to limit iterations using Claude Code's built-in `/loop` command.

> **Requires:** Claude Code v1.0.32+ (the `/loop` command was introduced in this version)

### Usage

**Unlimited (default):**
```
/autoresearch
Goal: Increase test coverage to 90%
```

**Bounded (N iterations):**
```
/loop 25 /autoresearch
Goal: Increase test coverage to 90%
```

This chains `/autoresearch` with `/loop 25`, running exactly 25 iteration cycles. After 25 iterations, Claude stops and prints a final summary.

### When to Use Bounded Loops

| Scenario | Recommendation |
|----------|---------------|
| Run overnight, review in morning | Unlimited (default) |
| Quick 30-min improvement session | `/loop 10 /autoresearch` |
| Targeted fix with known scope | `/loop 5 /autoresearch` |
| Exploratory — see if approach works | `/loop 15 /autoresearch` |
| CI/CD pipeline integration | `/loop N /autoresearch` (set N based on time budget) |

### Behavior with Loop Count

When a loop count is specified:
- Claude runs exactly N iterations through the autoresearch loop
- After iteration N, Claude prints a **final summary** with baseline → current best, keeps/discards/crashes
- If the goal is achieved before N iterations, Claude prints early completion and stops
- All other rules (atomic changes, mechanical verification, auto-rollback) still apply

## Setup Phase (Do Once)

1. **Read all in-scope files** for full context before any modification
2. **Define the goal** — What does "better" mean? Extract or ask for a mechanical metric:
   - Code: tests pass, build succeeds, performance benchmark improves
   - Content: word count target hit, SEO score improves, readability score
   - Design: lighthouse score, accessibility audit passes
   - If no metric exists → define one with user, or use simplest proxy (e.g. "compiles without errors")
3. **Define scope constraints** — Which files can you modify? Which are read-only?
4. **Define guard (optional)** — A command that must ALWAYS pass for a change to be kept. Use this to prevent regressions while optimizing the main metric (e.g., `npm test` must pass while optimizing benchmark time). If not specified, no guard is enforced.
5. **Create a results log** — Track every iteration (see `references/results-logging.md`)
6. **Establish baseline** — Run verification on current state AND guard (if set). Record as iteration #0
7. **Confirm and go** — Show user the setup, get confirmation, then BEGIN THE LOOP

## The Loop

Read `references/autonomous-loop-protocol.md` for full protocol details.

```
LOOP (FOREVER or N times):
  1. Review: Read current state + git history + results log
  2. Ideate: Pick next change based on goal, past results, what hasn't been tried
  3. Modify: Make ONE focused change to in-scope files
  4. Commit: Git commit the change (before verification)
  5. Verify: Run the mechanical metric (tests, build, benchmark, etc.)
  6. Guard: If guard is set, run the guard command
  7. Decide:
     - IMPROVED + guard passed (or no guard) → Keep commit, log "keep", advance
     - IMPROVED + guard FAILED → Revert, then try to rework the optimization
       (max 2 attempts) so it improves the metric WITHOUT breaking the guard.
       Never modify guard/test files — adapt the implementation instead.
       If still failing → log "discard (guard failed)" and move on
     - SAME/WORSE → Git revert, log "discard"
     - CRASHED → Try to fix (max 3 attempts), else log "crash" and move on
  8. Log: Record result in results log
  9. Repeat: Go to step 1.
     - If unbounded: NEVER STOP. NEVER ASK "should I continue?"
     - If bounded (N): Stop after N iterations, print final summary
```

## Critical Rules

1. **Loop until done** — Unbounded: loop until interrupted. Bounded: loop N times then summarize.
2. **Read before write** — Always understand full context before modifying
3. **One change per iteration** — Atomic changes. If it breaks, you know exactly why
4. **Mechanical verification only** — No subjective "looks good". Use metrics
5. **Automatic rollback** — Failed changes revert instantly. No debates
6. **Simplicity wins** — Equal results + less code = KEEP. Tiny improvement + ugly complexity = DISCARD
7. **Git is memory** — Every kept change committed. Agent reads history to learn patterns
8. **When stuck, think harder** — Re-read files, re-read goal, combine near-misses, try radical changes. Don't ask for help unless truly blocked by missing access/permissions

## Principles Reference

See `references/core-principles.md` for the 7 generalizable principles from autoresearch.

## Adapting to Different Domains

| Domain | Metric | Scope | Verify Command | Guard |
|--------|--------|-------|----------------|-------|
| Backend code | Tests pass + coverage % | `src/**/*.ts` | `npm test` | — |
| Frontend UI | Lighthouse score | `src/components/**` | `npx lighthouse` | `npm test` |
| ML training | val_bpb / loss | `train.py` | `uv run train.py` | — |
| Blog/content | Word count + readability | `content/*.md` | Custom script | — |
| Performance | Benchmark time (ms) | Target files | `npm run bench` | `npm test` |
| Refactoring | Tests pass + LOC reduced | Target module | `npm test && wc -l` | `npm run typecheck` |
| Security | OWASP + STRIDE coverage + findings | API/auth/middleware | `/autoresearch:security` | — |

Adapt the loop to your domain. The PRINCIPLES are universal; the METRICS are domain-specific.