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Agent Skill · 研究检索

expertise-file-design(专业知识档案设计)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

expertise-file-design 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 66,724。

总安装 259周安装 11GitHub Stars 61下载 91核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:expertise-file-design(专业知识档案设计)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/expertise-file-design
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill expertise-file-design
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/melodic-software/claude-code-plugins --skill expertise-file-design

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

设计 YAML 格式专业知识档案作为 Agent 心智模型。遵循 act-learn-reuse 上下文加速执行原则。限制行长保护上下文窗口完整性。expertise-file-design 属于研究检索类 Skill,可作为该场景下的辅助能力补充。强制对接实际代码库作为 truth source。

适用于领域特定 Agent 的知识体系建设。

来源仓库内路径:skills/expertise-file-design

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/melodic-software/claude-code-plugins --skill e…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

expertise-file-design 怎么安装?

在终端执行 npx skills add https://github.com/melodic-software/claude-code-plugins --skill expertise-f…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

expertise-file-design 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

expertise-file-design 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

expertise-file-design 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

expertise-file-design 用的人多吗?

公开数据是累计安装 259 次,近一周安装 11 次,下载 91 次,GitHub 61 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

expertise-file-design 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
expertise-file-design

专业知识档案设计 · 本页

25961接触敏感数据MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Expertise File Design

Guide for designing YAML expertise files that serve as mental models for agent experts.

MANDATORY: Act-Learn-Reuse Context

Expertise files are mental models, NOT sources of truth. They:

  • Accelerate agent execution by pre-loading domain knowledge
  • Are maintained by self-improve prompts, not humans
  • Validate against the actual codebase (source of truth)
  • Have enforced line limits to protect context windows

When to Use

  • Creating mental models for new domain-specific agents
  • Defining expertise schema structures (YAML)
  • Structuring knowledge for Act-Learn-Reuse workflows
  • Reviewing or auditing existing expertise file designs
  • Setting up line limits and section priorities

Expertise File Structure

Core Template

# {domain}/expertise.yaml
# Mental model for {domain} agent expert
# Last updated: {timestamp}
# Lines: {current}/{max}

overview:
  description: "Brief description of this domain"
  primary_technology: "Main tech/framework"
  architecture_pattern: "Key pattern used"

core_implementation:
  main_module:
    file: "path/to/main/file.ext"
    lines: approximate_line_count
    purpose: "What this module does"
    key_exports:
      - name: "FunctionOrClass"
        type: "function|class|constant"
        purpose: "Brief description"

  supporting_modules:
    - file: "path/to/support.ext"
      purpose: "Supporting functionality"

schema_structure:  # For database/API domains
  entities:
    entity_name:
      fields:
        - name: "field_name"
          type: "data_type"
          constraints: "nullable, unique, etc."
      relationships:
        - target: "other_entity"
          type: "one-to-many|many-to-many"

key_operations:
  operation_category:
    operation_name:
      function: "function_name"
      file: "path/to/file.ext"
      signature: "func(param: Type) -> ReturnType"
      logic: "Brief description of what it does"
      edge_cases:
        - "Important edge case 1"
        - "Important edge case 2"

patterns_and_conventions:
  naming:
    - "Convention description"
  error_handling:
    - "How errors are handled"
  data_flow:
    - "How data moves through system"

best_practices:
  - "Practice 1: Explanation"
  - "Practice 2: Explanation"

known_issues:
  - issue: "Issue description"
    workaround: "How to handle it"
    status: "open|resolved|wontfix"

integration_points:
  - system: "External system name"
    method: "How integration works"
    considerations: "Important notes"

testing_notes:
  - "How to test this domain"
  - "Key test scenarios"

Line Limits

Domain ComplexityMax LinesGuidance
Small/Focused300Single module, simple operations
Medium500-600Multiple modules, moderate complexity
Large/Complex800-1000Full subsystem, many operations
Absolute Max1000Never exceed - split into sub-experts

Section Priority

When approaching line limits, prioritize sections in this order:

  1. core_implementation - Essential for navigation
  2. key_operations - Critical for task execution
  3. best_practices - Prevents mistakes
  4. known_issues - Avoids wasted effort
  5. patterns_and_conventions - Nice to have
  6. testing_notes - Can reference external docs

Domain-Specific Templates

Database Domain

overview:
  database_system: "PostgreSQL|MySQL|MongoDB|etc"
  orm_pattern: "Raw SQL|ORM name|Query builder"
  connection_strategy: "Pooling|Single|Per-request"

schema_structure:
  tables:
    table_name:
      purpose: "What this table stores"
      primary_key: "id (UUID|INT)"
      fields: [...]
      indexes: [...]
      foreign_keys: [...]

key_operations:
  crud:
    create: {function: "", file: "", logic: ""}
    read: {function: "", file: "", logic: ""}
    update: {function: "", file: "", logic: ""}
    delete: {function: "", file: "", logic: ""}

  specialized:
    bulk_insert: {...}
    transaction_handling: {...}

API/Service Domain

overview:
  api_style: "REST|GraphQL|gRPC"
  auth_method: "JWT|OAuth|API Key"
  versioning: "URL|Header|None"

endpoints:
  resource_name:
    base_path: "/api/v1/resource"
    operations:
      list: {method: "GET", auth: "required", pagination: "cursor"}
      create: {method: "POST", auth: "required", validation: "..."}

request_response_patterns:
  success_format: {...}
  error_format: {...}

Frontend/UI Domain

overview:
  framework: "React|Vue|Angular|etc"
  state_management: "Redux|Zustand|Context|etc"
  styling: "CSS Modules|Tailwind|Styled Components"

component_hierarchy:
  pages:
    - name: "PageName"
      route: "/path"
      children: [...]

  shared:
    - name: "ComponentName"
      purpose: "Reusable for X"

state_structure:
  stores:
    store_name:
      shape: {...}
      actions: [...]

Seeding Strategy

When creating a new expertise file:

  1. Start minimal - Begin with overview and core_implementation only
  2. Let agent discover - Run self-improve to populate
  3. Iterate - Run self-improve until stable (no changes)
  4. Review - Human validates accuracy
  5. Maintain - Self-improve after every ACT

Anti-Patterns

PatternProblemSolution
Copy-pasting docsDuplicates source of truthReference files, don't copy
Including codeBloats file, goes staleReference by function name
No line limitsContext window overflowEnforce max lines strictly
Manual updatesHuman time wastedSelf-improve prompt only
Flat structureHard to navigateUse nested YAML sections

Validation Checklist

Before considering an expertise file complete:

  • Valid YAML syntax (no parse errors)
  • Under line limit for domain complexity
  • All file paths verified to exist
  • All function names verified accurate
  • Overview section complete
  • Key operations documented
  • Best practices included
  • Known issues captured

Related Skills

  • agent-expert-creation: Full agent expert workflow
  • self-improve-prompt-design: Maintaining expertise accuracy
  • meta-agentic-creation: Building experts that build experts

Last Updated: 2025-12-15

Version History

  • v1.0.0 (2025-12-26): Initial release

平台分布

Antigravity

28.95%
按下载量换算26

trae

22.44%
按下载量换算20

windsurf

15.9%
按下载量换算14

Claude Code

11.37%
按下载量换算10

Codex

7.16%
按下载量换算7

Gemini CLI

3.71%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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