Agent skill

Eval Harness

by cloudnative-co in cloudnative-co/claude-code-starter-kit

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.

MITAuto-check passedAI & LLM Engineering

Install Eval Harness

skills CLI

$ npx skills add cloudnative-co/claude-code-starter-kit --skill eval-harness -a claude-code

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

GitHub CLI

$ gh skill install cloudnative-co/claude-code-starter-kit eval-harness --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/cloudnative-co/claude-code-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/eval-harness .claude/skills/eval-harness && 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 "eval-harness" agent skill from https://github.com/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness into .claude/skills/eval-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-harness", 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/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness

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 cloudnative-co/claude-code-starter-kit --skill eval-harness -a codex

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

GitHub CLI

$ gh skill install cloudnative-co/claude-code-starter-kit eval-harness --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/cloudnative-co/claude-code-starter-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/eval-harness .agents/skills/eval-harness && 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 "eval-harness" agent skill from https://github.com/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness into .agents/skills/eval-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-harness", 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 cloudnative-co/claude-code-starter-kit --skill eval-harness -a cursor

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

GitHub CLI

$ gh skill install cloudnative-co/claude-code-starter-kit eval-harness --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/cloudnative-co/claude-code-starter-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/eval-harness .cursor/skills/eval-harness && 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 "eval-harness" agent skill from https://github.com/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness into .cursor/skills/eval-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-harness", 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/cloudnative-co/claude-code-starter-kit.git --path skills/eval-harness

--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 cloudnative-co/claude-code-starter-kit --skill eval-harness -a gemini-cli

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

GitHub CLI

$ gh skill install cloudnative-co/claude-code-starter-kit eval-harness --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/cloudnative-co/claude-code-starter-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/eval-harness .gemini/skills/eval-harness && 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 "eval-harness" agent skill from https://github.com/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness into .gemini/skills/eval-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-harness", 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 cloudnative-co/claude-code-starter-kit eval-harness

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 cloudnative-co/claude-code-starter-kit --skill eval-harness -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/cloudnative-co/claude-code-starter-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/eval-harness .github/skills/eval-harness && 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 "eval-harness" agent skill from https://github.com/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness into .github/skills/eval-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-harness", 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 cloudnative-co/claude-code-starter-kit --skill eval-harness -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 cloudnative-co/claude-code-starter-kit eval-harness --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/cloudnative-co/claude-code-starter-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/eval-harness .opencode/skills/eval-harness && 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 "eval-harness" agent skill from https://github.com/cloudnative-co/claude-code-starter-kit/tree/main/skills/eval-harness into .opencode/skills/eval-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-harness", 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: eval-harness
GitHub stars: 151
Used in: 10 other repos
Token cost: ~1.3k tokens
SKILL.md length: 235 words
Files: 1
Skills in repo: 8
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.

Works in 7 steps: Code-Based Grader → Model-Based Grader → Human Grader → …
Tasks that involve LLM evaluation
SKILL.md covers Philosophy, Eval Types, Grader Types and Eval Workflow, plus 4 more sections
Calls npm and claude

What it does

Eval Harness is an agent skill from cloudnative-co/claude-code-starter-kit. Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.

Its SKILL.md is about 1.3k 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 evaluation. The repository describes itself as: One-command setup of a complete Claude Code development environment with interactive wizard. The licence is MIT.

When your agent uses it

Tasks that involve LLM evaluation

Example prompts

“/eval-harness”

Workflow steps

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

Code-Based Grader
Model-Based Grader
Human Grader
Define (Before Coding)
Implement
Evaluate
Report

What it can do on your machine

Read from SKILL.md and the folder at commit f00e7ce. 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:
- npm
- claude
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.
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

Eval Harness loads about 1.3k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 235 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~30
When it runs · the whole SKILL.md, loaded when a task matches: ~1.3k

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 cloudnative-co/claude-code-starter-kit at commit f00e7ce, republished under its MIT licence (© cloudnative-co). 235 words, ~1,259 tokens.

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

name: eval-harness
description: Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.
when_to_use: Use when the user wants formal evals, pass/fail regression checks, or eval-driven development for AI behavior.

Eval Harness Skill

A formal evaluation framework for Claude Code sessions, implementing eval-driven development (EDD) principles.

Philosophy

Eval-Driven Development treats evals as the "unit tests of AI development":

Define expected behavior BEFORE implementation
Run evals continuously during development
Track regressions with each change

Eval Types

Capability Evals

Test if Claude can do something it couldn't before:

markdown

[CAPABILITY EVAL: feature-name]
Task: Description of what Claude should accomplish
Success Criteria:
  - [ ] Criterion 1
  - [ ] Criterion 2
  - [ ] Criterion 3
Expected Output: Description of expected result

Regression Evals

Ensure changes don't break existing functionality:

markdown

[REGRESSION EVAL: feature-name]
Baseline: git SHA (or a /checkpoint milestone name)
Tests:
  - existing-test-1: PASS/FAIL
  - existing-test-2: PASS/FAIL
  - existing-test-3: PASS/FAIL
Result: X/Y passed (previously Y/Y)

Grader Types

1. Code-Based Grader

Deterministic checks using code:

bash

# Check if file contains expected pattern
grep -q "export function handleAuth" src/auth.ts && echo "PASS" || echo "FAIL"

# Check if tests pass
npm test -- --testPathPattern="auth" && echo "PASS" || echo "FAIL"

# Check if build succeeds
npm run build && echo "PASS" || echo "FAIL"

2. Model-Based Grader

Have a separate instance (subagent) review open-ended outputs against a checklist:

markdown

[MODEL GRADER PROMPT]
Review the following code change and answer each question with YES/NO plus evidence:
1. Does it solve the stated problem?
2. Is it well-structured?
3. Are edge cases handled?
4. Is error handling appropriate?

Verdict: PASS/FAIL
Reasoning: [explanation]

3. Human Grader

Flag for manual review:

markdown

[HUMAN REVIEW REQUIRED]
Change: Description of what changed
Reason: Why human review is needed
Risk Level: LOW/MEDIUM/HIGH

Note: statistical metrics like pass@k require running the same task k times independently. If you truly need them, implement an automated script (e.g., a headless claude -p loop), not manual bookkeeping in an interactive session.

Eval Workflow

1. Define (Before Coding)

markdown

## EVAL DEFINITION: feature-xyz

### Capability Evals
1. Can create new user account
2. Can validate email format
3. Can hash password securely

### Regression Evals
1. Existing login still works
2. Session management unchanged
3. Logout flow intact

2. Implement

Write code to pass the defined evals.

3. Evaluate

bash

# Run capability evals
[Run each capability eval, record PASS/FAIL]

# Run regression evals
npm test -- --testPathPattern="existing"

# Generate report

4. Report

markdown

EVAL REPORT: feature-xyz
========================

Capability Evals:
  create-user:     PASS (attempts: 1)
  validate-email:  PASS (attempts: 2)
  hash-password:   PASS (attempts: 1)
  Overall:         3/3 passed

Regression Evals:
  login-flow:      PASS
  session-mgmt:    PASS
  logout-flow:     PASS
  Overall:         3/3 passed

Status: READY FOR REVIEW

Integration Patterns

Pre-Implementation

/eval define feature-name

Creates eval definition file at .claude/evals/feature-name.md

During Implementation

/eval check feature-name

Runs current evals and reports status

Post-Implementation

/eval report feature-name

Generates full eval report

Eval Storage

Store evals in project:

.claude/
  evals/
    feature-xyz.md      # Eval definition
    feature-xyz.log     # Eval run history
    baseline.json       # Regression baselines

Best Practices

Define evals BEFORE coding - Forces clear thinking about success criteria
Run evals frequently - Catch regressions early
Use code graders when possible - Deterministic > probabilistic
Human review for security - Never fully automate security checks
Keep evals fast - Slow evals don't get run
Version evals with code - Evals are first-class artifacts

Example: Adding Authentication

markdown

## EVAL: add-authentication

### Phase 1: Define (10 min)
Capability Evals:
- [ ] User can register with email/password
- [ ] User can login with valid credentials
- [ ] Invalid credentials rejected with proper error
- [ ] Sessions persist across page reloads
- [ ] Logout clears session

Regression Evals:
- [ ] Public routes still accessible
- [ ] API responses unchanged
- [ ] Database schema compatible

### Phase 2: Implement (varies)
[Write code]

### Phase 3: Evaluate
Run: /eval check add-authentication

### Phase 4: Report
EVAL REPORT: add-authentication
==============================
Capability: 5/5 passed
Regression: 3/3 passed
Status: SHIP IT

Files

Just SKILL.md in skills/eval-harness of cloudnative-co/claude-code-starter-kit.

Open the folder on GitHubat commit f00e7ce

Used in 10 other repositories

We found 15 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 10 other GitHub owners. This page covers the copy in cloudnative-co/claude-code-starter-kit, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Eval Harness 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.

Eval Harness compared with similar skills
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Eval Harness this skillcloudnative-co/claude-code-starter-kit	151	10 repos	~1.3k	Automated safety check: Pass	MIT	today
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs	13k	8 repos	~3k	Automated safety check: Pass	MIT	3 mo ago
Azure AI Projects Python SDKmicrosoft/skills	3.1k	6 repos	~2.8k	Automated safety check: Pass	MIT	yesterday
Fine-Tuning ExpertJeffallan/claude-skills	12k	1 repos	~1.7k	Automated safety check: Pass	MIT	4 days ago
Looperksimback/looper	710	—	~2.7k	Automated safety check: Notes	MIT	1 mo ago
Hugging Face Local Model Evalshuggingface/skills	11k	2 repos	~1.6k	Automated safety check: Pass	Apache-2.0	6 days ago

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Questions about Eval Harness

What does Eval Harness do?

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles. Eval Harness is an agent skill from cloudnative-co/claude-code-starter-kit. Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.

When should I use Eval Harness?

Eval Harness fits situations like: tasks that involve LLM evaluation.

How do I install Eval Harness in Claude Code?

Run `npx skills add cloudnative-co/claude-code-starter-kit --skill eval-harness -a claude-code`. Or copy the skill folder (skills/eval-harness in cloudnative-co/claude-code-starter-kit) into .claude/skills/eval-harness in your project. Claude Code loads it when a task matches its description.

How do I install Eval Harness in Codex?

Run `npx skills add cloudnative-co/claude-code-starter-kit --skill eval-harness -a codex`. Or copy the skill folder (skills/eval-harness in cloudnative-co/claude-code-starter-kit) into .agents/skills/eval-harness in your project. Codex loads it when a task matches its description.

Can I use Eval Harness 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 cloudnative-co/claude-code-starter-kit --skill eval-harness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eval-harness, .gemini/skills/eval-harness, .github/skills/eval-harness and .opencode/skills/eval-harness in your project.

What does Eval Harness need to run?

Going by SKILL.md and its folder, Eval Harness needs the command-line tools its instructions call (npm and claude).

Does Eval Harness access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Eval Harness 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 Eval Harness use?

Eval Harness 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 Eval Harness use?

About 1.3k tokens (SKILL.md is roughly 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 Eval Harness?

Skills that share tags, products or a category with Eval Harness: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), Azure AI Projects Python SDK (microsoft/skills, 3.1k stars), Fine-Tuning Expert (Jeffallan/claude-skills, 12k stars) and Looper (ksimback/looper, 710 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Eval Harness?

cloudnative-co (a GitHub organization) maintains it in cloudnative-co/claude-code-starter-kit, which has 151 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 7, 2026.

Source: cloudnative-co/claude-code-starter-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Eval Harness

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Eval Harness Skill

Philosophy

Eval Types

Capability Evals

Regression Evals

Grader Types

1. Code-Based Grader

2. Model-Based Grader

3. Human Grader

Eval Workflow

1. Define (Before Coding)

2. Implement

3. Evaluate

4. Report

Integration Patterns

Pre-Implementation

During Implementation

Post-Implementation

Eval Storage

Best Practices

Example: Adding Authentication

Files

Used in 10 other repositories

Compare with similar skills

Similar skills

More from cloudnative-co/claude-code-starter-kit

Related

Questions about Eval Harness