autoresearch is an agent workflow that repeatedly changes a project, verifies a measurable result, keeps or discards the change, and continues iterating toward a goal. It is for autonomous improvement tasks in Claude Code, OpenCode, and OpenAI Codex across domains with mechanical success measures. The catalogue contains its commands, hooks, skills, plugin, agent, and instruction.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/uditgoenka/autoresearch/shipgit clone --depth 1 https://github.com/uditgoenka/autoresearchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/uditgoenka/autoresearch/ship)<a href="https://agentmods.dev/commands/uditgoenka/autoresearch/ship"><img src="https://agentmods.dev/badge/commands/uditgoenka/autoresearch/ship.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.00981 |
| Opus 5 | $0.00010 | $0.00491 |
| Sonnet 5 | $0.00004 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
autoresearch:ship scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- autoresearch_ship — 98% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EXECUTE IMMEDIATELY.
Parse Arguments
Extract from $ARGUMENTS:
Target:or--target— what to ship (path, PR, artifact, deployment)--type <type>— override auto-detection: code-pr, code-release, deployment, content, docs, package, config--dry-run— validate everything but don't ship--auto— auto-approve if no errors found--force— skip non-critical items (blockers still enforced)--rollback— undo last ship action--monitor N— post-ship monitoring for N minutes--checklist-only— only generate checklist, don't execute--chain,--<subcommand>
Remaining text = description of what to ship.
Setup (if Target or Type unclear)
- Auto-detect ship type from context:
- Has uncommitted changes or PR → code-pr
- Has version bump / changelog → code-release
- Has Dockerfile / deploy config → deployment
- Has markdown / content files → content
- Has package.json version change → package
- If still unclear → AskUserQuestion (single batch): Q1 (What): "What are you shipping?" — code PR, release, deployment, content, docs, package Q2 (Target): "Specific target?" — current branch, specific PR, specific path Q3 (Mode): "How to ship?" — full workflow, dry-run only, checklist only If all clear → skip.
Phase 1: Identify
- Determine ship type (auto-detected or --type override)
- Identify target artifact(s)
- Map to domain-specific checklist
Phase 2: Inventory
Gather everything that will be shipped:
- Files changed (git diff)
- Dependencies affected
- Config changes
- Migration files
- Breaking changes
Phase 3: Checklist
Generate domain-specific checklist:
Code PR: tests pass, types check, lint clean, no secrets, PR description, reviewers assigned Release: version bumped, changelog updated, migration tested, rollback plan Deployment: env vars set, health checks configured, rollback ready, monitoring active Content: links valid, images optimized, SEO metadata, spell check Package: version bumped, README updated, breaking changes documented, CI green
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 121 lines · 20 tokens per session scan A a7a0f6f40282
autoresearch:ship is a command published in the GitHub repository uditgoenka/autoresearch (6,177 stars, last pushed 24d ago), licensed MIT. It adds 20 tokens to every session and 981 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
release
Walk the llmwiki release process step by step.
release-harn
Run the tag-first Harn release workflow.
release-plan
Command "release-plan" from alisunstar/OpenSunstar, covering /rd:release-plan — 发布计划, 先读, 执行, 产物 and 人工确认.
release
Standalone SDK release command for the BUILD repo. Not a workspace phase — runs independently after any number of implement/redteam cycles. Handles PyPI publishing, documentation deployment, and CI management for the kailash Python SDK and its framework packages.
create-pr
Push the current branch and open a pull request into main with a structured description derived from the branch's commits and issue references.
doc-changelog
Generation and maintenance of the project changelog.