eval-harness

eval-harness is a skill for Claude Code, Codex from Luohaothu/everything-codex. It costs 27 tokens per session (1,557 once invoked), scanned A, original, MIT.

A formal evaluation framework for Claude Code sessions based on evaluation-driven development, where expected agent behavior is defined and checked like software tests. It includes code-based, model-based, and human review methods, plus pass-rate measures.

In plain words
What is it for?
Use it to define capability or regression evaluations, check builds and tests, assess open-ended code changes, and track measures such as pass@1 or pass@3.
Why use it?
It helps reveal regressions and measure whether an AI coding workflow succeeds reliably across repeated attempts.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code.

Good fit Use it to define capability or regression evaluations, check builds and tests, assess open-ended code changes, and track measures such as pass@1 or pass@3.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/luohaothu/everything-codex/eval-harness
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Luohaothu/everything-codex --skill eval-harness
Clone the repo
git clone --depth 1 https://github.com/Luohaothu/everything-codex

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for eval-harness

README.md
[![agentmods](https://agentmods.dev/badge/skills/luohaothu/everything-codex/eval-harness/github.svg)](https://agentmods.dev/skills/luohaothu/everything-codex/eval-harness)
Your own site
<a href="https://agentmods.dev/skills/luohaothu/everything-codex/eval-harness"><img src="https://agentmods.dev/badge/skills/luohaothu/everything-codex/eval-harness/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for eval-harness

Your own site · 80×15
<a href="https://agentmods.dev/skills/luohaothu/everything-codex/eval-harness"><img src="https://agentmods.dev/badge/skills/luohaothu/everything-codex/eval-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,557 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.01557
Opus 5.5 $0.00011 $0.00623
Sonnet 5.5 $0.00005 $0.00311
Haiku 4.5 $0.00003 $0.00156

Measured 1mo ago against content hash 3dd943bf2519, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

eval-harness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

docs/zh-CN/skills/eval-harness/SKILL.md · 261 lines

How it starts

The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Eval Harness 技能

一个用于 Claude Code 会话的正式评估框架,实现了评估驱动开发 (EDD) 原则。

理念

评估驱动开发将评估视为 "AI 开发的单元测试":

  • 在实现 之前 定义预期行为
  • 在开发过程中持续运行评估
  • 跟踪每次更改的回归情况
  • 使用 pass@k 指标来衡量可靠性

评估类型

能力评估

测试 Claude 是否能完成之前无法完成的事情:

[能力评估:功能名称]
任务:描述 Claude 应完成的工作
成功标准:
  - [ ] 标准 1
  - [ ] 标准 2
  - [ ] 标准 标准 3
预期输出:对预期结果的描述

回归评估

确保更改不会破坏现有功能:

[回归评估:功能名称]
基线:SHA 或检查点名称
测试:
  - 现有测试-1:通过/失败
  - 现有测试-2:通过/失败
  - 现有测试-3:通过/失败
结果:X/Y 通过(之前为 Y/Y)

评分器类型

1. 基于代码的评分器

使用代码进行确定性检查:

# 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. 基于模型的评分器

使用 Claude 来评估开放式输出:

[MODEL GRADER PROMPT]
评估以下代码变更:
1. 它是否解决了所述问题?
2. 它的结构是否良好?
3. 是否处理了边界情况?
4. 错误处理是否恰当?

评分:1-5 (1=差,5=优秀)
推理:[解释]

3. 人工评分器

标记为需要手动审查:

[HUMAN REVIEW REQUIRED]
变更:对更改内容的描述
原因:为何需要人工审核
风险等级:低/中/高

指标

pass@k

"k 次尝试中至少成功一次"

  • pass@1:首次尝试成功率
  • pass@3:3 次尝试内成功率
  • 典型目标:pass@3 > 90%

pass^k

"所有 k 次试验都成功"

  • 更高的可靠性门槛
  • pass^3:连续 3 次成功
  • 用于关键路径

评估工作流程

1. 定义(编码前)

## 评估定义:功能-xyz

### 能力评估
1. 可以创建新用户账户
2. 可以验证电子邮件格式
3. 可以安全地哈希密码

### 回归评估
1. 现有登录功能仍然有效
2. 会话管理未改变
3. 注销流程完整

### 成功指标
- 能力评估的 pass@3 > 90%
- 回归评估的 pass^3 = 100%

2. 实现

编写代码以通过已定义的评估。

3. 评估

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

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

# Generate report

4. 报告

评估报告:功能-xyz
========================

能力评估:
  创建用户:    通过(通过@1)
  验证邮箱:    通过(通过@2)
  哈希密码:    通过(通过@1)
  总计:         3/3 通过

回归评估:
  登录流程:     通过
  会话管理:     通过
  登出流程:     通过
  总计:         3/3 通过

指标:
  通过@1: 67% (2/3)
  通过@3: 100% (3/3)

状态:准备就绪,待审核

集成模式

实施前

/eval define feature-name

在 .claude/evals/feature-name.md 处创建评估定义文件

Read the full file on GitHub · 261 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 261 lines · 27 tokens per session scan A 3dd943bf2519

Subscribe to this mod's changes

eval-harness is a skill published in the GitHub repository Luohaothu/everything-codex (25 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 1,557 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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