Skip to content
Automation
Skill

/autoresearch

Autonomous Goal-directed Iteration. Apply Karpathy's autoresearch principles to ANY task. Loops autonomously — modify, verify, keep/discard, repeat. 9 subcommands: plan, debug, fix, security, ship, scenario, predict, learn.

From plugin
dr-claw
1.1k174 skills
Install
$ npx -y skills add OpenLAIR/dr-claw --skill autoresearch --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/autoresearch

Context preview

The summary Claude sees to decide when to auto-load this skill.

Autonomous Goal-directed Iteration. Apply Karpathy's autoresearch principles to ANY task. Loops autonomously — modify, verify, keep/discard, repeat. 9 subcommands: plan, debug, fix, security, ship, scenario, predict, learn.

SKILL.md

autoresearch.SKILL.md
name: autoresearch
description: "Autonomous Goal-directed Iteration. Apply Karpathy's autoresearch principles to ANY task. Loops autonomously — modify, verify, keep/discard, repeat. 9 subcommands: plan, debug, fix, security, ship, scenario, predict, learn."
version: 1.8.2
license: MIT
metadata:
  author: uditgoenka/autoresearch
  version: "1.8.2"

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.

MANDATORY: Interactive Setup Gate

**CRITICAL — READ THIS FIRST BEFORE ANY ACTION:**

For ALL commands (`/autoresearch`, `/autoresearch:plan`, `/autoresearch:debug`, `/autoresearch:fix`, `/autoresearch:security`, `/autoresearch:ship`, `/autoresearch:scenario`, `/autoresearch:predict`, `/autoresearch:learn`):

1. **Check if the user provided ALL required context inline** (Goal, Scope, Metric, flags, etc.) 2. **If ANY required context is missing → you MUST use `AskUserQuestion` to collect it BEFORE proceeding to any execution phase.** DO NOT skip this step. DO NOT proceed without user input. 3. Each subcommand's reference file has an "Interactive Setup" section — follow it exactly when context is missing.

| Command | Required Context | If Missing → Ask | |---------|-----------------|-----------------| | `/autoresearch` | Goal, Scope, Metric, Direction, Verify | Batch 1 (4 questions) + Batch 2 (3 questions) from Setup Phase below | | `/autoresearch:plan` | Goal | Ask via `AskUserQuestion` per `references/plan-workflow.md` | | `/autoresearch:debug` | Issue/Symptom, Scope | 4 batched questions per `references/debug-workflow.md` | | `/autoresearch:fix` | Target, Scope | 4 batched questions per `references/fix-workflow.md` | | `/autoresearch:security` | Scope, Depth | 3 batched questions per `references/security-workflow.md` | | `/autoresearch:ship` | What/Type, Mode | 3 batched questions per `references/ship-workflow.md` | | `/autoresearch:scenario` | Scenario, Domain | 4-8 adaptive questions per `references/scenario-workflow.md` | | `/autoresearch:predict` | Scope, Goal | 3-4 batched questions per `references/predict-workflow.md` | | `/autoresearch:learn` | Mode, Scope | 4 batched questions per `references/learn-workflow.md` |

**YOU MUST NOT start any loop, phase, or execution without completing interactive setup when context is missing. This is a BLOCKING prerequisite.**

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:ship` | Universal shipping workflow: ship code, content, marketing, sales, research, or anything | | `/autoresearch:debug` | Autonomous bug-hunting loop: scientific method + iterative investigation until codebase is clean | | `/autoresearch:fix` | Autonomous fix loop: iteratively repair errors (tests, types, lint, build) until zero remain | | `/autoresearch:scenario` | Scenario-driven use case generator: explore situations, edge cases, and derivative scenarios | | `/autoresearch:predict` | Multi-persona swarm prediction: pre-analyze code from multiple expert perspectives before acting | | `/autoresearch:learn` | Autonomous codebase documentation engine: scout, learn, generate/update docs with validation-fix loop |

/autoresearch:security — Autonomous Security Audit

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
/autoresearch:security
Iterations: 10

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

# De
Read more
Ships withdr-claw

A Super AI Lab with massive AI Doctors as Assistants. Best IDE for Research via AI Power.

Get the whole plugin
Stats
1,091
Stars
119
Forks
Active
Maintenance
JavaScript
Language
6d ago
Last commit
6mo ago
Created

Repo: OpenLAIR/dr-claw

Other skills on dr-claw.