Agent skill

Bench

by AlphaLab-USTC in AlphaLab-USTC/OhMyCode

Run OhMyCode benchmarks — score any provider/model with token tracking.

MITAuto-check passedAI & LLM Engineering

Install Bench

skills CLI

$ npx skills add AlphaLab-USTC/OhMyCode --skill bench -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install AlphaLab-USTC/OhMyCode bench --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/AlphaLab-USTC/OhMyCode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/bench .claude/skills/bench && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "bench" agent skill from https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench into .claude/skills/bench/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bench", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add AlphaLab-USTC/OhMyCode --skill bench -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install AlphaLab-USTC/OhMyCode bench --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AlphaLab-USTC/OhMyCode.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/bench .agents/skills/bench && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "bench" agent skill from https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench into .agents/skills/bench/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bench", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add AlphaLab-USTC/OhMyCode --skill bench -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install AlphaLab-USTC/OhMyCode bench --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AlphaLab-USTC/OhMyCode.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/bench .cursor/skills/bench && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "bench" agent skill from https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench into .cursor/skills/bench/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bench", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/AlphaLab-USTC/OhMyCode.git --path .claude/skills/bench

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add AlphaLab-USTC/OhMyCode --skill bench -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install AlphaLab-USTC/OhMyCode bench --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AlphaLab-USTC/OhMyCode.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/bench .gemini/skills/bench && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "bench" agent skill from https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench into .gemini/skills/bench/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bench", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install AlphaLab-USTC/OhMyCode bench

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add AlphaLab-USTC/OhMyCode --skill bench -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/AlphaLab-USTC/OhMyCode.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/bench .github/skills/bench && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "bench" agent skill from https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench into .github/skills/bench/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bench", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add AlphaLab-USTC/OhMyCode --skill bench -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install AlphaLab-USTC/OhMyCode bench --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AlphaLab-USTC/OhMyCode.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/bench .opencode/skills/bench && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "bench" agent skill from https://github.com/AlphaLab-USTC/OhMyCode/tree/main/.claude/skills/bench into .opencode/skills/bench/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bench", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: bench
GitHub stars: 131
Token cost: ~941 tokens
SKILL.md length: 326 words
Files: 1
Skills in repo: 10
Repo updated: Apr 2, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Run OhMyCode benchmarks — score any provider/model with token tracking.

Works in 3 steps: Run the Benchmark → Read Results → Analyze Failures
User wants to benchmark
SKILL.md covers When to Use, Input, Step 1 — Run the Benchmark and Step 2 — Read Results, plus 5 more sections
Calls python3

What it does

Bench is an agent skill from AlphaLab-USTC/OhMyCode. Run OhMyCode benchmarks — score any provider/model with token tracking. Use when user wants to benchmark, evaluate, test performance, or compare models.

Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering LLM observability. The repository describes itself as: Minimal and Customizable CC-Style Coding Agent. The licence is MIT.

When your agent uses it

User wants to benchmark
Test performance

Example prompts

“/bench”

Requirements

Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

Run the Benchmark
Read Results
Analyze Failures

What it can do on your machine

Read from SKILL.md and the folder at commit 4d1bb28. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bench loads about 941 tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 326 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~40
When it runs · the whole SKILL.md, loaded when a task matches: ~941

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AlphaLab-USTC/OhMyCode at commit 4d1bb28, republished under its MIT licence (© AlphaLab-USTC). 326 words, ~941 tokens.

Download SKILL.mdSave it as .claude/skills/bench/SKILL.md (or your agent's skills folder).

name: bench
description: Run OhMyCode benchmarks — score any provider/model with token tracking. Use when user wants to benchmark, evaluate, test performance, or compare models.

OhMyCode Benchmark

One-command benchmarking: run 8 SWE-bench-style coding tasks through OhMyCode, track token usage (in/out), and produce a scorecard.

Works with any provider and model — uses whatever is configured in ~/.ohmycode/config.json or overridden via CLI args.

When to Use

User says "run benchmark", "bench", "score", "evaluate", "test performance"
User wants to compare models or providers
After major code changes, to verify agent capabilities still work

Input

$ARGUMENTS — optional filters and overrides.

Argument	Example	Effect
(empty)	`/bench`	Full suite, current config
task filter	`/bench fib,bug`	Only matching tasks
`--dry-run`	`/bench --dry-run`	Validate task definitions without LLM

Step 1 — Run the Benchmark

bash

python3 benchmarks/run_bench.py $ARGUMENTS 2>&1 | tee bench_run.log

Override provider/model for comparison

bash

# Test with a different model
python3 benchmarks/run_bench.py --provider openai --model gpt-4o-mini 2>&1 | tee bench_run.log

# Test with Anthropic
python3 benchmarks/run_bench.py --provider anthropic --model claude-sonnet-4-20250514 2>&1 | tee bench_run.log

# Test with custom endpoint
python3 benchmarks/run_bench.py --base-url http://localhost:8080/v1 --api-key test 2>&1 | tee bench_run.log

Step 2 — Read Results

The harness outputs:

Terminal report — table with per-task pass/fail, tokens, time
bench_results.json — machine-readable results for comparison

Key metrics to report:

Score: X/8 tasks passed
Tokens in: total prompt tokens across all tasks
Tokens out: total completion tokens across all tasks
Total tokens: in + out
Time: wall-clock seconds

Step 3 — Analyze Failures

If any tasks failed:

Read the reason column in the report
Check bench_results.json for the error field
Classify: is it a model capability issue, or an OhMyCode bug?
For OhMyCode bugs → fix and re-run /bench (closed-loop)

Benchmark Tasks

#	Task	Category	What It Tests
1	fibonacci	code-gen	Create a function from spec
2	bug-fix-round	bug-fix	Find and fix an off-by-one error
3	test-generation	test-gen	Write tests for existing code
4	refactor-preserve	refactor	Improve code without breaking tests
5	grep-replace	tool-use	Multi-file search and replace
6	stack-module	code-gen	Create module + tests from scratch
7	type-error-fix	bug-fix	Fix a TypeError in existing code
8	code-comprehension	comprehension	Read code and explain the algorithm

Adding New Tasks

Edit benchmarks/suite.py:

python

BenchTask(
    name="your-task",
    category="bug-fix",
    prompt="The task description for the agent...",
    setup=lambda d: (d / "code.py").write_text("..."),  # prepare files
    validate=lambda d: (True, "reason"),                 # check result
    max_turns=10,
)

Then append to BENCH_SUITE list.

Model Comparison Workflow

To compare two models:

bash

python3 benchmarks/run_bench.py --model gpt-4o 2>&1 | tee bench_gpt4o.log
cp bench_results.json bench_gpt4o.json

python3 benchmarks/run_bench.py --model gpt-4o-mini 2>&1 | tee bench_mini.log
cp bench_results.json bench_mini.json

Then compare the JSON files for score and token efficiency.

/run-tests — run unit tests (the benchmark runs these too as Phase 1)
/gen-tests — generate tests (task #3 in the benchmark tests this capability)

Files

Just SKILL.md in .claude/skills/bench of AlphaLab-USTC/OhMyCode.

Open the folder on GitHubat commit 4d1bb28

Compare with similar skills

Bench next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bench compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Bench this skillAlphaLab-USTC/OhMyCode	131	—	~941	Automated safety check: Pass	MIT	6 mo ago
Phx Examplesoliver-kriska/claude-elixir-phoenix	565	—	~1k	Automated safety check: Pass	MIT	2 days ago
Phx Quickoliver-kriska/claude-elixir-phoenix	565	—	~805	Automated safety check: Pass	MIT	2 days ago
Phx Quickoliver-kriska/claude-elixir-phoenix	565	—	~811	Automated safety check: Pass	MIT	2 days ago
Langfuse Integration Pagelangfuse/langfuse-docs	246	—	~3.7k	Automated safety check: Pass	MIT	today
Langfuselangfuse/skills	299	—	~2.1k	Automated safety check: Notes	MIT	6 days ago

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Questions about Bench

What does Bench do?

Run OhMyCode benchmarks — score any provider/model with token tracking. Bench is an agent skill from AlphaLab-USTC/OhMyCode. Run OhMyCode benchmarks — score any provider/model with token tracking.

When should I use Bench?

Bench fits situations like: user wants to benchmark; test performance.

How do I install Bench in Claude Code?

Run `npx skills add AlphaLab-USTC/OhMyCode --skill bench -a claude-code`. Or copy the skill folder (.claude/skills/bench in AlphaLab-USTC/OhMyCode) into .claude/skills/bench in your project. Claude Code loads it when a task matches its description.

How do I install Bench in Codex?

Run `npx skills add AlphaLab-USTC/OhMyCode --skill bench -a codex`. Or copy the skill folder (.claude/skills/bench in AlphaLab-USTC/OhMyCode) into .agents/skills/bench in your project. Codex loads it when a task matches its description.

Can I use Bench in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AlphaLab-USTC/OhMyCode --skill bench -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bench, .gemini/skills/bench, .github/skills/bench and .opencode/skills/bench in your project.

What does Bench need to run?

Going by SKILL.md and its folder, Bench needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Bench access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bench safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bench use?

Bench is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bench use?

About 941 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bench?

Skills that share tags, products or a category with Bench: Phx Examples (oliver-kriska/claude-elixir-phoenix, 565 stars), Phx Quick (oliver-kriska/claude-elixir-phoenix, 565 stars), Phx Quick (oliver-kriska/claude-elixir-phoenix, 565 stars) and Langfuse Integration Page (langfuse/langfuse-docs, 246 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bench?

AlphaLab-USTC (a GitHub user) maintains it in AlphaLab-USTC/OhMyCode, which has 131 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on April 2, 2026.

Source: AlphaLab-USTC/OhMyCode on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Bench

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

OhMyCode Benchmark

When to Use

Input

Step 1 — Run the Benchmark

Override provider/model for comparison

Step 2 — Read Results

Step 3 — Analyze Failures

Benchmark Tasks

Adding New Tasks

Model Comparison Workflow

Related Skills

Files

Compare with similar skills

Similar skills

More from AlphaLab-USTC/OhMyCode

Related

Questions about Bench