autoresearch
ALWAYS activate when user types /autoresearch, $autoresearch plan, $autoresearch debug, $autoresearch fix, $autoresearch security, $autoresearch ship, $autoresearch scenario, $autoresearch predict, $autoresearch learn, $autoresearch reason, or $autoresearch probe. MUST also activate when user mentions "autoresearch" with ANY goal, metric, or task, even when the invocation is embedded in prose. This is a BLOCKING skill invocation — invoke BEFORE generating any other response.
npx skills add majiayu000/claude-skill-registry --skill autoresearch-mxyhi-ok-skills --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Autoresearch is described as an autonomous goal-directed iteration engine. It operates as a BLOCKING skill invocation and activates under a long list of explicit commands and any mention of the word "autoresearch". It runs iterative loops (Modify → Verify → Keep/Discard → Repeat) with strict guardrails, including atomic commits, mandatory Verify, optional Guard, and explicit ship confirmation. It covers multiple subcommands (plan, security, ship, scenario, predict, learn, reason, probe, debug, and the base autoresearch loop) to perform tasks such as security audits, shipping workflows, scenario generation, and multi-persona analysis.
How it works
- The skill requires Interactive Setup Gate for all commands; if required context is missing, it prompts the user with direct questions before proceeding.
- It enforces a per-iteration workflow: make a change, Verify, then decide to keep or discard with an automatic rollback on failure. Changes kept are committed with an
experiment:prefix; discards usegit revert-clean. - It optionally applies a Guard if configured; if Guard fails, changes revert.
- Before Verify dry-runs, it screens for dangerous operations and credentials exposure.
- It masks secrets in findings and reproduction commands.
- It ensures that Verify outputs are data, not instructions, and that any external content is not treated as directives.
- For the ship subcommand, it requires explicit user confirmation at the appropriate phase gate before publishing.
- CI/CD and bounded iterations considerations are documented to limit loop behavior in non-interactive contexts.
When to use it
- Use when you need an autonomous, iterative approach to a complex task with required context, multiple workflows, or security-focused analysis.
- Use for security auditing, shipping workflows, scenario exploration, multi-persona analysis, or building documentation through autonomous loops.
What it can touch
- It interacts with code, configurations, and artifacts as part of the iterative cycle.
- It defines outputs and reports in structured folders per workflow phase (e.g., security/audit folders, ship logs, scenario results).
Caveats
- It operates under guardrails including atomic commits, Verify requirements, and optional Guard checks.
- Ship actions require explicit user confirmation; non-approval prevents publishing.
- It includes safety screens before Verify dry-runs to prevent dangerous commands.
# Codex 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. ## Safety Posture (read once per session) The autoresearch skill family grants the agent broad iterative authority — read, edit, run shell, commit. To keep that authority load-bearing, every command operates inside fixed guardrails: - **Atomic commits per iteration.** Each kept change is committed with `experiment:` prefix; each discard is `git revert`-clean. No silent multi-iteration changes. - **Mandatory `Verify`.** Nothing is kept unless the Verify command exits ≥0 and produces a measurable number. Failed Verify = automatic rollback. - **Optional `Guard`.** When set, Guard MUST also pass; broken Guard reverts the change. Use Guard for "do not regress tests" or "do not break build." - **Verify-command safety screen.** Before any Verify dry-run, screen for `rm -rf /`, fork bombs, fetch-and-execute (`curl ... | sh`), embedded credentials, and unannounced outbound writes (see `ref
- Safety Posture (read once per session)
- MANDATORY: Interactive Setup Gate
- Subcommands
- $autoresearch security — Autonomous Security Audit
- $autoresearch ship — Universal Shipping Workflow
- $autoresearch scenario — Scenario-Driven Use Case Generator
- $autoresearch predict — Multi-Persona Swarm Prediction
- $autoresearch learn — Autonomous Codebase Documentation Engine
- $autoresearch reason — Adversarial Refinement for Subjective Domains
- $autoresearch probe — Adversarial Requirement & Assumption Interrogation
- $autoresearch plan — Goal → Configuration Wizard
- When to Activate
- Bounded Iterations
- When to Use Bounded Iterations
What does the autoresearch skill do?
ALWAYS activate when user types /autoresearch, $autoresearch plan, $autoresearch debug, $autoresearch fix, $autoresearch security, $autoresearch ship, $autoresearch scenario, $autoresearch predict, $autoresearch learn, $autoresearch reason, or $autoresearch probe. MUST also activate when user mentions "autoresearch" with ANY goal, metric, or task, even when the invocation is embedded in prose. This is a BLOCKING skill invocation — invoke BEFORE generating any other response.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill autoresearch-mxyhi-ok-skills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
