Codex Autoresearch
Measured, resumable optimization loop with baseline, correctness gate, and evidence ledger
Test report
- Verdict
- Tested · Works
- Score
- Tested
- Jul 21, 2026
- Environment
- Claude Code 2.x (agent harness)
- Upstream re-checked
- Aug 10, 2026 · f0fac23
I built a toy Node project (sumTo via array+reduce, a bench.mjs printing METRIC seconds= and a checks.mjs), then ran the loop two ways under a temp HOME. Baseline (no skill): I just rewrote the function to an accumulator loop and re-ran bench (0.7297s -> 0.3652s) — a faster file, no record. Skill: setup wrote a session (autoresearch.md/.jsonl/.sh), doctor --check-benchmark confirmed the METRIC contract, next+log captured baseline 0.7234, then the keep packet logged 0.3542 with checks passing (exit 0, "checks OK"), created scoped git commit 8d4e192 touching only lib/sum.mjs, attached an ASI note (hypothesis/evidence/next-action), and finalize-preview produced a review-branch plan flagging maturity "experimental". Decisive difference: when I fed a faster-but-wrong change (closed-form +1), the packet's checks exited 1 and the CLI forced status checks_failed as the only allowed status, refusing the keep — the baseline path has no such regression gate.
Scored on four weighted criteria — install, triggering, output vs. baseline, docs. How scoring works
- Installs cleanly 5/5
- Triggers reliably 5/5
- Output vs. baseline 8/10
- Docs & honesty 4/5
What Codex Autoresearch does
Turns a vague "make it faster/smaller" request into a measured loop: it records a benchmark baseline, runs one scoped change per packet, re-runs correctness checks, and logs each result (metric, decision, evidence, next action) to a resumable session file with a scoped git commit. Triggers on benchmark-driven optimization (test runtime, bundle size, latency, memory), qualitative quality-gap research, resuming an existing autoresearch session, or preparing a review-branch finalization. Backed by a Node CLI (autoresearch.mjs) that runs the benchmark and checks commands locally.
How to install Codex Autoresearch
git clone --depth 1 https://github.com/TheGreenCedar/codex-autoresearch.git /tmp/codex-autoresearch-src
mkdir -p ~/.claude/skills
cp -R /tmp/codex-autoresearch-src/plugins/codex-autoresearch/skills/codex-autoresearch ~/.claude/skills/codex-autoresearch
# NOTE: this is a Codex PLUGIN, not a standalone skill. The SKILL.md drives a Node CLI that
# lives OUTSIDE the skill folder at /tmp/codex-autoresearch-src/plugins/codex-autoresearch/scripts/autoresearch.mjs
# Requirements: Node >= 24. On first run the CLI hydrates a runtime (downloads the matching
# GitHub release tarball with sha256 verification, or build locally from the clone).
# Run commands from the package root, e.g.:
# node /tmp/codex-autoresearch-src/plugins/codex-autoresearch/scripts/autoresearch.mjs setup --cwd <project> --name <s> --metric-name seconds --direction lower --benchmark-command "<cmd printing METRIC name=value>" --checks-command "<cmd>"
# Intended install path is Codex's /plugins picker (TheGreenCedar -> codex-autoresearch), which bundles the CLI.
Skills live in ~/.claude/skills/ (global) or .claude/skills/
(per-project). Restart Claude Code after installing.
Commands — how to trigger Codex Autoresearch
-
/codex-autoresearchMeasured, resumable optimization loop with baseline, correctness gate, and evidence ledger
It also activates on plain-language prompts like these:
-
Start a new Codex Autoresearch loop -
Resume and inspect the current autoresearch run -
Show the autoresearch dashboard and quality gaps
Frequently asked questions
- Is the Codex Autoresearch skill free?
- Yes. The skill itself is free from TheGreenCedar/codex-autoresearch. SkillProof publishes the install command and an independent test verdict at no cost.
- Does Codex Autoresearch work with Claude Code?
- We tested it with Claude Code 2.x (agent harness) on Jul 21, 2026. Verdict: Tested · Works. I built a toy Node project (sumTo via array+reduce, a bench.mjs printing METRIC seconds= and a checks.mjs), then ran the loop two ways under a temp HOME. Baseline (no skill): I just rewrote the function to an accumulator loop and re-ran bench (0.7297s -> 0.3652s) — a faster file, no record. Skill: setup wrote a session (autoresearch.md/.jsonl/.sh), doctor --check-benchmark confirmed the METRIC contract, next+log captured baseline 0.7234, then the keep packet logged 0.3542 with checks passing (exit 0, "checks OK"), created scoped git commit 8d4e192 touching only lib/sum.mjs, attached an ASI note (hypothesis/evidence/next-action), and finalize-preview produced a review-branch plan flagging maturity "experimental". Decisive difference: when I fed a faster-but-wrong change (closed-form +1), the packet's checks exited 1 and the CLI forced status checks_failed as the only allowed status, refusing the keep — the baseline path has no such regression gate.
- What is the Codex Autoresearch SkillProof Score?
- 8.8/10 — installs cleanly 5/5, triggers reliably 5/5, output vs. baseline 8/10, docs & honesty 4/5.
- How do I install Codex Autoresearch?
- Copy the install command from this page, run it in your terminal, and restart Claude Code. Skills live in ~/.claude/skills/ (global) or .claude/skills/ inside a project.
- Can I use Codex Autoresearch with Cursor, Copilot, Gemini CLI, Codex or other AI tools?
- The SKILL.md format is native to Claude (Claude Code, Desktop, claude.ai). The instructions inside adapt to other assistants: Cursor rules, GitHub Copilot instructions, Windsurf rules, Custom GPTs, AGENTS.md for OpenAI Codex, and GEMINI.md for Google Gemini CLI — our conversion guides cover each, and the free converter on the tools page does the wrapping for you.