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.
npx agentmods add skills/luohaothu/everything-codex/eval-harnessnpx skills add Luohaothu/everything-codex --skill eval-harnessgit clone --depth 1 https://github.com/Luohaothu/everything-codexWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00027 | $0.01557 |
| Opus 5 | $0.00014 | $0.00779 |
| Sonnet 5 | $0.00005 | $0.00311 |
| Haiku 4.5 | $0.00003 | $0.00156 |
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 2d 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.
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
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.
- 2d ago First seen · 261 lines · 27 tokens per session scan A 3dd943bf2519
eval-harness is a skill published in the GitHub repository Luohaothu/everything-codex (24 stars, last pushed 21d ago), licensed MIT. It adds 27 tokens to every session and 1,557 once invoked, about $0.0001 per session on Opus 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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