agent-skills-standard
💡 摘要
Agent Skills Standard是一个模块化框架,用于在各种工具之间分发和同步AI编码标准。
🎯 适合人群
🤖 AI 吐槽: “看起来很能打,但别让配置把人劝退。”
风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发);API Key/Token 的获取、存储与泄露风险;文件读写范围与路径穿越风险。以最小权限运行,并在生产环境启用前审计代码与依赖。
Agent Skills Standard 🚀
The open standard for High-Density AI coding instructions. Make your AI smarter, faster, and more consistent.
Agent Skills Standard is a modular framework to distribute, sync, and version-control engineering standards across all major AI agents (Cursor, Claude Code, GitHub Copilot, Windsurf, Gemini, Antigravity, and custom LLM workflows).
💡 What is this?
Think of Agent Skills Standard as a universal instruction manual for your AI assistant.
Usually, when you use AI for work, you have to constantly remind it of your "house rules" (e.g., "Make sure to handle errors this way" or "Use this specific layout"). This project allows teams to package those rules into "Skills" that you can plug into any AI tool instantly.
Why does this matter?
- For Managers: Ensure your entire team writes high-quality code that follows your company's standards, regardless of which AI tool they use.
- For Non-IT Users: You don't need to know how the rules are written; you just run one command to "upgrade" your AI with professional-grade engineering knowledge.
- For Teams: No more "Hey, why did the AI write it this way?"—everyone’s AI uses the same playbook.
⚡ The Problem: "The Context Wall"
Modern AI coding agents are powerful, but they struggle when managing project-wide rules:
- Information Overload: Providing too many instructions at once confuses the AI and makes it forgetful.
- Version Chaos: Every team member has a different version of "best practices" floating around their local computer.
- Wasted Space: Long, wordy instructions "eat up" the AI's limited memory (the Context Window), making it more expensive and less effective.
🛠 The Solution: Digital DNA for AI
Agent Skills Standard treats instructions as versioned dependencies, much like software libraries.
- 🎯 Smart Loading: We use a "Search-on-Demand" pattern. The AI only looks at detailed examples when it specifically needs them, saving its memory for your actual code.
- 🚀 High-Density Language: We use a specialized "Compressed Syntax" that is 40% more efficient than normal English. This means the AI understands more while using fewer resources.
- 🔁 One-Click Sync: A single command ensures your AI tool stays up-to-date with your team's latest standards.
✨ Features
- 🛡️ Multi-Agent Support: Out-of-the-box mapping for Cursor, Claude Dev, GitHub Copilot, and more.
- 📦 Modular Registry: Don't load everything. Only enable the skills your project actually uses (e.g.,
Flutter + BLoC + Clean Architecture). - 🔄 Dynamic Re-detection: Automatically re-enables excluded skills if matching dependencies (like
Retrofit,Room, orNavigation) are added to your project. - 🔒 Secure Overrides: Lock specific files in your project so they never get overwritten by the central registry.
- 📊 Semantic Tagging: Skills are tagged with triggers that tell the AI exactly when to apply them.
� Token Economy & Optimization
To ensure AI efficiency, this project follows a strict Token Economy. Every skill is audited for its footprint in the AI's context window.
📏 Our Standards
- High-Density: Core rules in
SKILL.mdare kept under 70 lines. - Efficiency: Target < 500 tokens per primary skill file.
- Progressive Disclosure: Heavy examples, checklists, and implementation guides are moved to the
references/directory and are only loaded by the agent when specific context matches.
🛠️ Token Calculation
We provide a built-in tool in the CLI to estimate and track the token footprint:
pnpm calculate-tokens
This command:
- Scans all
SKILL.mdfiles in the registry. - Calculates character-based token estimates.
- Updates
skills/metadata.jsonwith category metrics (total tokens, avg/skill, and identifying the largest skills).
By maintaining a "Lean Registry," we ensure that your AI assistant remains fast and focused, preserving the majority of its context window for your actual project code.
🔒 Privacy & Feedback
Feedback Reporter Skill
By default, the CLI syncs a common/feedback-reporter skill that enables you to report when AI makes mistakes or when skill guidance needs improvement. This helps us improve skills for everyone.
What Gets Shared (Only if You Report):
- Skill category and name
- Issue description (written by you or generated by AI)
- Skill Instruction: Exact quote from the skill that was violated
- Actual Action: What the AI did instead
- Decision Reason: Why the AI chose that approach
- Optional context (framework version, scenario)
- Optional AI Model name
- NO code, NO project details, NO personal information
How to Opt-Out:
Add to .skillsrc:
skills: common: exclude: ['feedback-reporter']
Manual Feedback
If you notice a skill needs improvement, you can manually send feedback using (no installation required):
npx agent-skills-standard feedback
How it works:
- Cross-Platform: Works instantly on Windows, MacOS, and Linux via
npx. - The CLI attempts to submit your feedback automatically via our High-Density Feedback Backend (hosted on Render.com).
- No token needed: We handle the GitHub integration securely on the server.
Or via structured comments in your code:
// @agent-skills-feedback // Skill: react/hooks // Issue: AI suggested unsafe pattern // Suggestion: Add guidance for this case
Privacy First: We never collect usage telemetry or analytics. Feedback is only shared if you explicitly trigger it.
�🚀 Quick Start (Get running in 60s)
Consume engineering standards in your project instantly.
1. Run the CLI
npx agent-skills-standard@latest init
The interactive wizard will detect your stack and setup your .skillsrc.
2. Sync Standards
npx agent-skills-standard@latest sync
What happened?
- Dynamic Re-detection: The CLI scans your project dependencies (e.g.,
build.gradle,pubspec.yaml,package.json). If you've recently added a library that matches an excluded skill, the CLI will automatically re-enable it and update your.skillsrc. - Distribution: The CLI fetched the latest High-Density Skills and distributed them into your hidden agent folders (e.g.,
.cursor/skills/,.github/skills/). Your AI is now "upgraded" with your team's standards.
3. Validate Skills (For Contributors)
npx agent-skills-standard@
优点
- 模块化和灵活的框架。
- 支持多种AI工具。
- 提高代码质量一致性。
- 非技术用户易于使用。
缺点
- 可能需要初始设置时间。
- 依赖外部工具。
- 新用户的学习曲线。
- 可能存在版本冲突。
相关技能
免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。
版权归原作者所有 HoangNguyen0403.
