ai-agent-bench · git:20260919.a9f7da5 · 2026-09-19 · sha256 000f291fe9127b2b
ai-agent-bench git:20260919.a9f7da5A
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--- name: ai-agent-bench description: "Compare Claude Code and Codex on the same code task, with isolated worktrees, common checks, time, and cost." user-invocable: true allowed-tools: Glob, Grep, Read, Bash, Edit, Write --- # AI agent bench Compare agents only with the same task, starting commit, and outcome check. The harness preserves result branches and removes temporary worktrees. Create `<repo>/.agent-bench.toml`: ```toml prompt = "prompts/task.md" start_branch = "main" # or start_commit agents = ["claude", "codex"] outer_check = "./scripts/full_check.sh" inner_check = "uv run pytest tests/integration/test_x.py -q" ``` `outer_check` proves the real outcome before and after, and measures wall time. `inner_check` gives agents fast feedback. Require a clean repo, available CLIs, and a passing `outer_check`. Confirm agents and run ID, then run trials sequentially to avoid load-biased timing: ```bash uv run python <skill>/scripts/run_trial.py --repo "$REPO" --config "$REPO/.agent-bench.toml" --agent "$AGENT" --run "$RUN_ID" ``` Results go to `eval-results/<task>/<agent>/run-<id>-<timestamp>/`. Record unexpected behavior in `ai-agent-bench-anomalies.md` per [anomalies](references/anomalies.md). Aggregate with `scripts/parse_transcript.py --aggregate <run-dirs> --output comparison.json --render-report comparison.md`. Report gates, branches, time delta, tokens, and cost. Never rank a failed trial. For plugin behavior rather than a real code task, use the bounded Pydantic runner owned by `eval-regression`. Never commit on the user's branch. A repeated run creates a new timestamped result and preserves prior evidence.