Borrowing it
Nothing to install: this file belongs to shenjingnan/xiaozhi-client. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/shenjingnan/xiaozhi-client/main/.agents/skills/dev-workflow-checker/SKILL.mdgit clone --depth 1 https://github.com/shenjingnan/xiaozhi-clientWrote 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.
[](https://agentmods.dev/skills/shenjingnan/xiaozhi-client/dev-workflow-checker)<a href="https://agentmods.dev/skills/shenjingnan/xiaozhi-client/dev-workflow-checker"><img src="https://agentmods.dev/badge/skills/shenjingnan/xiaozhi-client/dev-workflow-checker.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.01039 |
| Opus 5 | $0.00010 | $0.00519 |
| Sonnet 5 | $0.00004 | $0.00208 |
| Haiku 4.5 | $0.00002 | $0.00104 |
Grade A, and why
dev-workflow-checker 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 8d 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.
What it actually says
开发流程检查技能
当用户进行代码修改后，此技能确保执行必要的质量检查命令，同时遵循务实开发理念。
技能描述
该技能会在用户完成代码修改后，自动提醒并执行相关的开发流程检查，确保代码质量和类型安全，但不追求过度的完美标准。
技能使用原则
- 保证质量，但避免过度检查：执行必要的检查，但不追求完美的检查流程
- 实用功能优先，理论完美次之：解决实际的代码问题比预防各种可能更重要
- 简单解决方案优于复杂方案：优先选择直接有效的检查方式
- 务实开发指导：评估检查的必要性，避免过度检查
检查内容
前端应用 (src/web)
当修改前端代码时，执行以下检查：
pnpm typecheck- TypeScript 类型检查pnpm lint- Biome linter 检查pnpm test- 运行测试套件pnpm check:all- 运行所有质量检查（如果需要全面检查）
后端应用 (src/server)
当修改后端代码时，执行以下检查：
pnpm typecheck- TypeScript 类型检查pnpm lint- Biome linter 检查pnpm test- 运行测试套件pnpm check:all- 运行所有质量检查（如果需要全面检查）
使用场景
- 完成代码修改后：自动提醒用户执行相应的检查命令
- 提交代码前：确保所有检查都通过
- PR 创建前：验证代码质量标准
- 集成测试前：确保基本质量门控通过
检查流程
前端代码修改流程
# 1. 类型检查
pnpm typecheck
# 2. 代码风格检查
pnpm lint
# 3. 运行测试
pnpm test
# 4. 全面检查（可选）
pnpm check:all
后端代码修改流程
# 1. 类型检查
pnpm typecheck
# 2. 代码风格检查
pnpm lint
# 3. 运行测试
pnpm test
# 4. 全面检查（可选）
pnpm check:all
质量标准
必须通过的检查
- ✅ TypeScript 类型检查（零错误）
- ✅ Biome linter 检查（符合项目代码风格）
- ✅ 测试套件（所有测试通过）
推荐检查
- ✅ 代码覆盖率（达到80%目标）
- ✅ 拼写检查
- ✅ 重复代码检查
错误处理
类型检查失败
- 检查
any类型的使用 - 验证 React 组件属性类型
- 确保路径别名正确使用
Linter 检查失败
- 代码格式不符合项目标准
- 导入顺序不正确
- 未使用的变量或导入
测试失败
- 检查测试用例的逻辑
- 验证 mock 配置
- 确认测试环境设置
项目特定要求
零容忍政策
- 禁止使用
any类型：必须使用具体类型或unknown - 测试文件类型安全：同样禁止
any类型 - React 组件属性类型：使用具体的 React 组件属性类型
路径别名要求
- 跨目录导入必须使用正确的路径别名
- 避免使用相对路径导入其他目录
- 按照最佳实践排序导入语句
本地化规范
- 代码注释使用中文
- 测试用例描述使用中文
- 变量和函数名继续使用英文
自动化建议
建议在以下场景自动触发检查：
- Git pre-commit hook
- CI/CD pipeline
- IDE 保存时自动检查
- Pull Request 创建时
注意事项
- 区分应用目录：根据修改的文件选择正确的检查命令
- 错误优先级：先修复类型错误，再处理风格问题
- 性能考虑：全面检查耗时较长，可在关键时刻执行
- 团队协作：确保所有开发人员遵循相同的检查标准
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.
- 8d ago First seen · 135 lines · 20 tokens per session scan A 578ee0110e51
dev-workflow-checker is a skill published in the GitHub repository shenjingnan/xiaozhi-client (337 stars, last pushed 4d ago), licensed MIT. It adds 20 tokens to every session and 1,039 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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