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/regressiongit 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/regression)<a href="https://agentmods.dev/commands/uditgoenka/autoresearch/regression"><img src="https://agentmods.dev/badge/commands/uditgoenka/autoresearch/regression.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 | $0.00034 | $0.02482 |
| Opus 5 | $0.00017 | $0.01241 |
| Sonnet 5 | $0.00007 | $0.00496 |
| Haiku 4.5 | $0.00003 | $0.00248 |
Grade C, and why
autoresearch:regression scanned grade C with 2 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
Verify-command screen (no `rm -rf` / `curl|sh`); worktree cleanup + prune on crash; data-migration refuses any non-allowlisted DB URL; probe auto-skips non-interactively; chained `ship` never auto-deploys. Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Verify-command screen (no `rm -rf` / `curl|sh`); worktree cleanup + prune on crash; data-migration refuses any non-allowlisted DB URL; probe auto-skips non-interactively; chained `ship` never auto-deploys. Copies of this mod
1 near-identical copy found in the catalogue:
- autoresearch:regression — 94% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EXECUTE IMMEDIATELY.
A regression is a green→red transition ONLY. The gate orchestrates the project's OWN test/bench/snapshot/migrate commands (it is a protocol, not a bundled framework), captures baseline behavior in an isolated git worktree, re-runs the candidate, and reports a tiered ship/no-ship verdict.
Parse Arguments
Extract from $ARGUMENTS:
Base:or--base— base ref to diff against. Default:git merge-base HEAD main(elsemain/master).Scope:or--scope— file globs limiting the change surface.--select auto|full|affected— test selection (defaultauto).auto= use the detected affected-test mapper if available, else FULL suite. Never a silent subset.--samples N— SCORE samples/side (default 7).--noise-band %— perf tolerance (default 5%).--matrix— opt-in matrix axis (OFF by default).--max-runs N— ceiling (default 200).--baseline-cache(default on) — reusebaseline/<full-sha>/by SHA.Baseline: <prebuilt-ref>— bypass capture.--probe(default) /--probe deep/--no-probe.--predict --reason --debug --fix --fix-cycles N --evals --evals-interval N --chain <targets>and--<sub>shorthand.Iterations:— repeat-axis count for--select/repeat sweeps.
Setup / Probe-on-launch
- Auto-detect per-dimension verify commands:
package.jsonscripts,Makefile,nx, migrate config, bench/snapshot/size scripts. - AskUserQuestion (single batch) to confirm detected commands + base ref + which dimensions to run.
- Auto-skip probe when CI / no-TTY /
--mode autonomous/ complete-config / chained-handoff — log the inferred config instead of asking.
Classification Phase (first-class, before any differential)
Establish the baseline green-set per dimension, then tag each unit. Match by test-id first, then path.
| State | Meaning | Gated? |
|---|---|---|
regression-eligible |
green on baseline | YES — only green→red counts |
pre-existing |
red→red (already failing) | no — excluded |
new-coverage |
absent→red (brand-new test) | no — new coverage, ungated |
flaky |
nondeterministic on baseline | no — routed to flakiness SCORE |
baseline-unavailable |
dimension never green | no — advisory only |
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 · 111 lines · 34 tokens per session scan C c352c5c2a4df
autoresearch:regression is a command published in the GitHub repository uditgoenka/autoresearch (6,116 stars, last pushed 23d ago), licensed MIT. It adds 34 tokens to every session and 2,482 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
drift
Read the Genesis build phases document: docs/architecture/genesis-v3-build-phases.md.
challenge
Read the specified design doc section.
thoth:dashboard
Alias for status --dashboard; manage the local dashboard backed by .thoth ledgers.
run-autoresearch
Run an autonomous experiment loop via the Autoresearch Orchestrator agent.
onboard
/anty:onboard — QUEST-Based Conversational Interview.
next-issue
Fetch the next ready-for-agent issue by priority.