Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add xu-xiang/everything-claude-code-zh --skill "eval-harness"
Install specific skill from multi-skill repository
# Description
为 Claude Code 会话提供的正式评测框架,实现了评测驱动开发(Eval-Driven Development,EDD)原则
# SKILL.md
name: eval-harness
description: 为 Claude Code 会话提供的正式评测框架,实现了评测驱动开发(Eval-Driven Development,EDD)原则
tools: Read, Write, Edit, Bash, Grep, Glob
评测套件技能(Eval Harness Skill)
一个为 Claude Code 会话提供的正式评测框架,实现了评测驱动开发(Eval-Driven Development,EDD)原则。
核心理念(Philosophy)
评测驱动开发(EDD)将评测(Evals)视为“AI 开发的单元测试”:
- 在实现代码之“前”定义预期行为
- 在开发过程中持续运行评测
- 跟踪每次变更带来的回归(Regressions)
- 使用 pass@k 指标来衡量可靠性
评测类型
能力评测(Capability Evals)
测试 Claude 是否能够完成之前无法完成的任务:
[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
回归评测(Regression Evals)
确保变更不会破坏现有功能:
[REGRESSION EVAL: feature-name]
Baseline: SHA or checkpoint name
Tests:
- existing-test-1: PASS/FAIL
- existing-test-2: PASS/FAIL
- existing-test-3: PASS/FAIL
Result: X/Y passed (previously Y/Y)
评分器(Grader)类型
1. 基于代码的评分器(Code-Based Grader)
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(Model-Based Grader)
使用 Claude 评估开放式输出:
[MODEL GRADER PROMPT]
Evaluate the following code change:
1. Does it solve the stated problem?
2. Is it well-structured?
3. Are edge cases handled?
4. Is error handling appropriate?
Score: 1-5 (1=poor, 5=excellent)
Reasoning: [explanation]
3. 人工评分器(Human Grader)
标记以供人工审查:
[HUMAN REVIEW REQUIRED]
Change: Description of what changed
Reason: Why human review is needed
Risk Level: LOW/MEDIUM/HIGH
指标(Metrics)
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
- 典型目标:pass@3 > 90%
pass^k
“k 次试验全部成功”
- 更高的可靠性门槛
- pass^3:连续 3 次成功
- 用于关键路径(Critical Paths)
评测工作流
1. 定义(编码前)
## 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
### Success Metrics
- pass@3 > 90% for capability evals
- pass^3 = 100% for regression evals
2. 实现
编写代码以通过定义的评测。
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
EVAL REPORT: feature-xyz
========================
Capability Evals:
create-user: PASS (pass@1)
validate-email: PASS (pass@2)
hash-password: PASS (pass@1)
Overall: 3/3 passed
Regression Evals:
login-flow: PASS
session-mgmt: PASS
logout-flow: PASS
Overall: 3/3 passed
Metrics:
pass@1: 67% (2/3)
pass@3: 100% (3/3)
Status: READY FOR REVIEW
集成模式
实现前(Pre-Implementation)
/eval define feature-name
在 .claude/evals/feature-name.md 创建评测定义文件。
实现中(During Implementation)
/eval check feature-name
运行当前评测并报告状态。
实现后(Post-Implementation)
/eval report feature-name
生成完整的评测报告。
评测存储
在项目中存储评测:
.claude/
evals/
feature-xyz.md # 评测定义
feature-xyz.log # 评测运行历史
baseline.json # 回归基线
最佳实践
- 在编码之“前”定义评测 —— 强制对成功准则进行清晰思考。
- 频繁运行评测 —— 尽早发现回归。
- 随着时间推移跟踪 pass@k —— 监控可靠性趋势。
- 尽可能使用代码评分器 —— 确定性(Deterministic)优于概率性(Probabilistic)。
- 安全相关的由人工审查 —— 永远不要完全自动化安全检查。
- 保持评测快速 —— 缓慢的评测往往不会被运行。
- 将评测与代码一同进行版本控制 —— 评测是一等公民产物(First-class Artifacts)。
示例:添加身份验证
## 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 (pass@3: 100%)
Regression: 3/3 passed (pass^3: 100%)
Status: SHIP IT
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.