Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
Write code evaluators for known failure modes with objective rules.
Install Write Code Eval
$ npx skills add ai-evals-course/evals-skills --skill write-code-eval -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ai-evals-course/evals-skills write-code-eval --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ai-evals-course/evals-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/write-code-eval .claude/skills/write-code-eval && rm -rf skills-srcUse ~/.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/
Install the "write-code-eval" agent skill from https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-eval into .claude/skills/write-code-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-code-eval", 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 install https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-evalType 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.
$ npx skills add ai-evals-course/evals-skills --skill write-code-eval -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ai-evals-course/evals-skills write-code-eval --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-evals-course/evals-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/write-code-eval .agents/skills/write-code-eval && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "write-code-eval" agent skill from https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-eval into .agents/skills/write-code-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-code-eval", 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.
$ npx skills add ai-evals-course/evals-skills --skill write-code-eval -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ai-evals-course/evals-skills write-code-eval --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-evals-course/evals-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/write-code-eval .cursor/skills/write-code-eval && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "write-code-eval" agent skill from https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-eval into .cursor/skills/write-code-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-code-eval", 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 https://github.com/ai-evals-course/evals-skills.git --path skills/write-code-eval--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ai-evals-course/evals-skills --skill write-code-eval -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ai-evals-course/evals-skills write-code-eval --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-evals-course/evals-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/write-code-eval .gemini/skills/write-code-eval && rm -rf skills-srcUse ~/.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/
Install the "write-code-eval" agent skill from https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-eval into .gemini/skills/write-code-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-code-eval", 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.
$ gh skill install ai-evals-course/evals-skills write-code-evalInstalls 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).
$ npx skills add ai-evals-course/evals-skills --skill write-code-eval -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ai-evals-course/evals-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/write-code-eval .github/skills/write-code-eval && rm -rf skills-srcUse ~/.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/
Install the "write-code-eval" agent skill from https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-eval into .github/skills/write-code-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-code-eval", 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.
$ npx skills add ai-evals-course/evals-skills --skill write-code-eval -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ai-evals-course/evals-skills write-code-eval --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-evals-course/evals-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/write-code-eval .opencode/skills/write-code-eval && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "write-code-eval" agent skill from https://github.com/ai-evals-course/evals-skills/tree/main/skills/write-code-eval into .opencode/skills/write-code-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-code-eval", 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
write-code-eval- GitHub stars
- 1.5k
- Token cost
- ~385 tokens
- SKILL.md length
- 202 words
- Files
- 2
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Write code evaluators for known failure modes with objective rules.
- Works in 3 steps: State the rule and identify the trace… → Implement the check in the project's… → Test known passes and failures,…
- Code can check the rule from a trace
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Without a reference answer
What it does
Write Code Eval is an agent skill from ai-evals-course/evals-skills. Write code evaluators for known failure modes with objective rules. Use when code can check the rule from a trace, with or without a reference answer. Use write-judge-prompt when the rule requires interpretation.
Its SKILL.md is about 390 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in AI & LLM Engineering. The repository describes itself as: Skills that guide AI coding agents to help you build product-specific AI evals. The licence is Apache-2.0.
When your agent uses it
- Code can check the rule from a trace
- Without a reference answer
Example prompts
- “/write-code-eval”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- State the rule and identify the trace fields or reference data the check needs. If the rule requires interpretation, use write-judge-prompt.
- Implement the check in the project's language and eval framework. Return a result and a reason in the format that framework expects.
- Test known passes and failures, including borderline cases. Run the check on available traces and inspect mistakes. If the rule uses a…
What it can do on your machine
Read from SKILL.md and the folder at commit 80d5f7b. 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
No scripts in the folder and no shell commands in SKILL.md.
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
Write Code Eval loads about 385 tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 202 words of instructions outside code blocks.
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 ai-evals-course/evals-skills at commit 80d5f7b, republished under its Apache-2.0 licence (© ai-evals-course). 202 words, ~385 tokens.
Download SKILL.mdSave it as
.claude/skills/write-code-eval/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- write-code-eval
- description
- Write code evaluators for known failure modes with objective rules. Use when code can check the rule from a trace, with or without a reference answer. Use `write-judge-prompt` when the rule requires interpretation.
Write a code evaluator
Start with a failure mode found through error analysis. Write one check for that failure mode, much like a unit test that asserts what should hold for each trace.
- State the rule and identify the trace fields or reference data the check needs. If the rule requires interpretation, use
write-judge-prompt. - Implement the check in the project's language and eval framework. Return a result and a reason in the format that framework expects.
- Test known passes and failures, including borderline cases. Run the check on available traces and inspect mistakes. If the rule uses a proxy for human judgment, compare its results with human labels.
Examples
| Failure mode | Possible check |
|---|---|
| Invalid output structure | Parse the output and check required fields |
| Missing or forbidden text | Match a string or pattern |
| Citation not in retrieved documents | Compare cited IDs with retrieved IDs |
| Bad tool call | Check arguments against the tool schema or run the call in a safe test environment |
| Wrong value | Compare the output with a reference value |
Choose the check from the failure rule. For a failure with both objective and interpretive parts, check the objective part with code and use a judge for the rest.
© ai-evals-course, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/write-code-eval of ai-evals-course/evals-skills.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit 80d5f7b
Compare with similar skills
Write Code Eval 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Write Code Eval this skillai-evals-course/evals-skills | 1.5k | — | ~385 | Automated safety check: Pass | Apache-2.0 | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 6 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| Peft Fine TuningOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.3k | Automated safety check: Pass | MIT | |
| 1passwordtrpc-group/trpc-agent-go | 1.8k | 15 repos | ~656 | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Write Code Eval
What does Write Code Eval do?
Write code evaluators for known failure modes with objective rules. Write Code Eval is an agent skill from ai-evals-course/evals-skills. Write code evaluators for known failure modes with objective rules.
When should I use Write Code Eval?
Write Code Eval fits situations like: code can check the rule from a trace; without a reference answer.
How do I install Write Code Eval in Claude Code?
Run `npx skills add ai-evals-course/evals-skills --skill write-code-eval -a claude-code`. Or copy the skill folder (skills/write-code-eval in ai-evals-course/evals-skills) into .claude/skills/write-code-eval in your project. Claude Code loads it when a task matches its description.
How do I install Write Code Eval in Codex?
Run `npx skills add ai-evals-course/evals-skills --skill write-code-eval -a codex`. Or copy the skill folder (skills/write-code-eval in ai-evals-course/evals-skills) into .agents/skills/write-code-eval in your project. Codex loads it when a task matches its description.
Can I use Write Code Eval 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 ai-evals-course/evals-skills --skill write-code-eval -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/write-code-eval, .gemini/skills/write-code-eval, .github/skills/write-code-eval and .opencode/skills/write-code-eval in your project.
What does Write Code Eval need to run?
SKILL.md names no scripts, command-line tools or credentials: Write Code Eval is instructions for the agent only.
Does Write Code Eval 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 Write Code Eval 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 Write Code Eval use?
Write Code Eval is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Write Code Eval use?
About 385 tokens (SKILL.md is roughly 1.5k 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 Write Code Eval?
Skills that share tags, products or a category with Write Code Eval: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), Peft Fine Tuning (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Write Code Eval?
ai-evals-course (a GitHub organization) maintains it in ai-evals-course/evals-skills, which has 1,468 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 24, 2026.
Source: ai-evals-course/evals-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.