DEDUPEDAuthorization notice. harness2 is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.
Who it is forDeveloper who already uses Codex as a coding agent and wants harness improvements tuned to that executor
The problemHarness edits that help one executor may not carry over to another, and you have no way to check without a controlled run.
The outcomeA refinement run on Codex whose results are stored separately so you can compare it against an OpenCode run.
What you need first
- Linux, Python 3.12 and uv for installation
- No credentials needed for the local demo (harness2-demo)
- Model-backed runs need Node.js 20+, the Google Cloud CLI, a Vertex AI project and model IDs in .env, and gcloud application-default login
- LAB needs Pandoc and Poppler; WorkBuddy-Bench needs Docker
- Model-backed benchmark runs incur API costs
Steps
- Read the Codex executor section in docs/SETUP.md and finish its prerequisites.
- Install a benchmark: harness2-setup jb
- Run with Codex: harness2 --bench jb --k 1 --mode parallel --substrate cx --max-tasks 1
- Use a fresh HARNESS2_RUNS_DIR when changing models or task selection.
- Judge and report with matching flags: harness2-judge --bench jb --k 1 --mode parallel --substrate cx
Prompt for your agent
In google-research/harness2, run one JobBench task with --substrate cx and --k 1 --mode parallel, then judge it with matching flags. Verify the run completes under its own runs directory and that network restrictions are configured first.
Caveat. Codex runs with its sandbox disabled and executors get open web access, so run it only in an isolated environment, and confirm whether judge and report also need the substrate flag in the experiment guide.
About harness2
A framework that lets an AI agent keep improving its own setup (prompts, tools, memory, skills) while the model itself stays unchanged. Part of this week's top 10 repos: ranked #2 on Repo Radar. View google-research/harness2 on GitHub.
More with harness2
- Audit which harness edits were adopted and why Read the adopted harnesses and reflection notes from a run to learn which prompt or tool edits drove a gain.
- Watch an agent improve its own setup in 5 minutes, no API key Run the built-in demo to see both recursion modes edit a harness with real Python executions and zero credentials.
- Boost an office, web or coding agent on WorkBuddy tasks Refine an agent's harness on one WorkBuddy-Bench subset to see if office, web or code results improve.
- Test whether harness edits lift your agent on legal tasks Run one LAB legal-work task with refinement, then judge and report, to see if edits beat the base harness.
- Run a clean benchmark with network limits against rubric leaks Lock down network access before evaluating so an agent cannot look up public benchmark answers.
- Compare parallel and sequential refinement on the same task Run the same benchmark task in both recursion modes to pick the cheaper or stronger refinement strategy.
- Resume a long refinement run after it stops midway Re-issue the same command to continue a multi-task run without redoing finished tasks.
Disclaimer
Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page