Skip to content
Back to skills

Ai Agent Bench

ASecurity

Compare Claude Code and Codex on the same real code-change task with isolated worktrees, identical gates, transcripts, time, and cost.

  • 3 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added September 12, 2026
ai-agentspythongobashgit

Works with

  • claude code
  • cli

Security analysis

A100/100

Pro scans all 7 files and shows the line behind each finding

Scanned September 12, 2026

npx -y skills add thedixitjain/the-mega-skill-library --skill ai-agent-bench --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Ai Agent Bench?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Ai Agent Bench
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/thedixitjain-ai-agent-bench/badge)](https://www.skillsdirectory.com/skills/thedixitjain-ai-agent-bench)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: ai-agent-bench
description: "Compare Claude Code and Codex on the same real code-change task with isolated worktrees, identical gates, transcripts, time, and cost."
allowed-tools: "Glob, Grep, Read, Bash, Edit, Write"
category: ai-agents-and-harness
source_repo: hashgraph-online/awesome-codex-plugins
source_path: "plugins/reidemeister94/development-skills/skills/ai-agent-bench/SKILL.md"
source_url: https://github.com/hashgraph-online/awesome-codex-plugins/blob/HEAD/plugins/reidemeister94/development-skills/skills/ai-agent-bench/SKILL.md
---


# 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 = "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
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 documented by `eval-regression` and `scripts/run_evals.py`.

Never commit on the user's branch. A repeated run creates a new timestamped result and preserves prior evidence.

---

**Source:** [`hashgraph-online/awesome-codex-plugins`](https://github.com/hashgraph-online/awesome-codex-plugins) → `plugins/reidemeister94/development-skills/skills/ai-agent-bench/SKILL.md`

Files in this skill

  • SKILL.md2.2 KB
  • references/anomalies.md2.1 KB
  • scripts/monitor.py4.5 KB
  • scripts/parse_transcript.py54.3 KB
  • scripts/pricing.json1.4 KB
  • scripts/run_evals.py46.6 KB
  • scripts/run_trial.py25.9 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…