代码审查方法
审查清单
功能正确性
- 代码实现符合需求
- 边界情况处理正确
- 错误处理完善
代码质量
- 命名清晰易懂
- 函数职责单一
- 避免重复代码
- 注释必要且准确
安全性
- 输入验证
- SQL注入防护
- XSS防护
- 认证授权正确
性能
- 无明显性能问题
- 数据库查询优化
- 避免N+1查询
可维护性
- 代码结构清晰
- 易于测试
- 遵循项目规范
代码审查方法,包含审查清单、常见问题、最佳实践
| Publisher | echoVic |
| Repository | boss-skill |
| Skill name | tech-lead/code-review |
| Stars | 562 |
| Forks | 51 |
| Bundled files | Instructions only |
| License | MIT |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Everything the model needs lives in the instructions — no extra files to sync.
Published by echoVic on GitHub. Read the source before you install it.
Install the Tech Lead/Code Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
https://github.com/echoVic/boss-skill/tree/main/skill/skills/tech-lead/code-reviewAny agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/echoVic/boss-skill.git /tmp/boss-skill
mkdir -p .claude/skills
cp -r /tmp/boss-skill/skill/skills/tech-lead/code-review .claude/skills/echovic-tech-lead-code-reviewEnable Tech Lead/Code Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.
AI skills are plain Markdown instructions rather than provider-specific code, so Tech Lead/Code Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
代码审查方法,包含审查清单、常见问题、最佳实践
Because you install it once and use it with any model. Tech Lead/Code Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/echoVic/boss-skill/tree/main/skill/skills/tech-lead/code-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.
As many as you like. As long as a model supports skills, you can use Tech Lead/Code Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Yes. It is published on GitHub by echoVic under the MIT license. You only pay your own AI provider for the tokens you use.
An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.
A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.
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