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Agent Skill · 研究检索

skill-creator(技能创建器)

skill-creator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

skill-creator 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,权限为调用外部服务;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 13,815。

总安装 9,072周安装 367GitHub Stars 39下载 2,848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:skill-creator(技能创建器)
来源仓库:https://github.com/bobmatnyc/claude-mpm-skills
仓库路径:skills/skill-creator
安装命令:
npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill skill-creator
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/bobmatnyc/claude-mpm-skills --skill skill-creator

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。

skill-creator 指导创建或重构高效专用技能模块。倡导渐进披露设计,保持入口简洁而细节丰富。适用于扩展 Claude 能力边界时的工程实践参考。包含模板与检查清单,提升技能可维护性与用户体验。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/skill-creator

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/bobmatnyc/claude-mpm-skills --skill skill-crea…;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

    它需要调用外部服务,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

skill-creator 怎么安装?

在终端执行 npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill skill-creator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-creator 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。

skill-creator 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

skill-creator 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。

skill-creator 用的人多吗?

公开数据是累计安装 9,072 次,近一周安装 367 次,下载 2,848 次,GitHub 39 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。

skill-creator 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

  • 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

  • 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
skill-creator

技能创建器 · 本页

9,07239调用外部服务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

Skill Creator

Overview

Create effective skills that extend Claude's capabilities through specialized knowledge, workflows, and tools. Skills are modular packages that transform Claude from a general-purpose agent into a specialized agent with procedural knowledge for specific domains.

This skill exemplifies its own teachings by using progressive disclosure to keep the entry point lean while providing deep detail in reference files.

When to Use This Skill

Activate when:

  • Creating a new skill from scratch
  • Updating or refactoring an existing skill
  • Adding progressive disclosure to monolithic skills
  • Understanding skill structure and best practices
  • Planning skill components (scripts, references, assets)
  • Packaging skills for distribution

Core Principles

  1. Example-Driven Design: Start with concrete usage examples, not abstract concepts
  2. Progressive Disclosure: Keep entry point <200 lines (optimal: 140-160), detailed content in references
  3. Reusable Components: Extract scripts for repeated code, references for knowledge, assets for templates
  4. Imperative Voice: Use verb-first instructions throughout (not second person)
  5. Purpose-Built Resources: Each component should solve specific repetitive needs

What Skills Provide

Four Core Capabilities:

  1. Specialized workflows - Multi-step procedures for specific domains
  2. Tool integrations - Instructions for working with file formats or APIs
  3. Domain expertise - Company-specific knowledge, schemas, business logic
  4. Bundled resources - Scripts, references, and assets for complex tasks

Three-Level Loading System:

  1. Metadata (name + description) - Always in context (~100 words)
  2. SKILL.md body - When skill triggers (<200 lines, optimal: 140-160)
  3. Bundled resources - As needed by Claude (unlimited)

Quick Start

Six-Step Creation Process

Step 1: Understand with Concrete Examples Gather 3-5 realistic usage examples. Ask: "What would users say to trigger this skill?" and "What tasks should it accomplish?" → Complete guide

Step 2: Plan Reusable Components Analyze examples to identify: scripts (repeated code), references (domain knowledge), assets (templates). → Planning guide

Step 3: Initialize Skill Run scripts/init_skill.py <skill-name> --path <output-directory> to generate template structure. → Initialization details

Step 4: Edit Skill Implement scripts/references/assets, then update SKILL.md using imperative voice. Apply progressive disclosure if >150 lines. → Editing guide

Step 5: Package and Validate Run scripts/package_skill.py <path/to/skill-folder> to validate and create distributable zip. → Packaging guide

Step 6: Iterate Use on real tasks, notice struggles, update skill accordingly. → Iteration guide

Skill Anatomy

skill-name/
├── SKILL.md (required)           # Entry point with frontmatter + markdown
├── scripts/ (optional)           # Executable code (Python/Bash)
├── references/ (optional)        # Documentation loaded as needed
└── assets/ (optional)            # Templates, images, files for output

Component Guidelines:

  • Scripts: When same code is repeatedly rewritten or deterministic execution needed
  • References: For detailed specs, workflows, schemas, API docs (150-500 lines each)
  • Assets: For templates, boilerplate, images, fonts used in outputs
  • Entry Point: Core workflow, navigation, reminders (140-160 lines optimal)

→ Complete structure guide

Progressive Disclosure Pattern

When to apply: Skills >150 lines total

Implementation:

  1. Add progressive_disclosure frontmatter with summary, when_to_use, quick_start
  2. Reduce entry point to 140-160 lines (core workflow + navigation)
  3. Create 3-5 reference files (150-500 lines each)
  4. Organize by topic: structure, workflow, best practices, examples
  5. Add navigation section linking all references

Benefits:

  • Entry loads only essential content
  • Deep detail available when needed
  • Better organization and maintainability
  • 20-30% reduction in entry point size

→ Complete progressive disclosure guide

Meta-example: This skill-creator demonstrates progressive disclosure:

  • Entry: 150 lines (28% reduction from 209)
  • References: 5 files with complete implementation details
  • Recently optimized: mcp-builder (160 lines), testing-anti-patterns (140 lines)

Navigation

Core Concepts

  • 🏗️ Skill Structure - Anatomy, components (scripts/references/assets), progressive disclosure architecture. Load when planning skill layout or understanding resource types.

Step-by-Step Process

  • 🔄 Creation Workflow - Complete 6-step process from examples to iteration. Load when creating new skill or following structured workflow.

Design Patterns

  • 📊 Progressive Disclosure - Three-level loading, implementation guide, anti-patterns, examples. Load when refactoring skills >150 lines or optimizing context usage.

Quality Standards

  • ✅ Best Practices - Writing style, metadata quality, content organization, anti-patterns. Load when writing/reviewing skill content or ensuring quality.

Real-World Examples

  • 📚 Examples - Complete skill examples: mcp-builder, testing-anti-patterns, pdf-editor, brand-guidelines, database-builder, frontend-builder. Load when starting new skill or seeking patterns.

Key Reminders

  • Start with examples - 3-5 concrete usage scenarios before designing
  • Use init script - scripts/init_skill.py creates proper structure automatically
  • Imperative voice - "To accomplish X, do Y" (not "should do X")
  • Progressive disclosure - Entry <200 lines, details in references (for skills >150 lines)
  • Avoid duplication - Information lives in ONE place (entry summary, reference detail)
  • Component clarity - Scripts for code, references for knowledge, assets for templates
  • Validate before sharing - scripts/package_skill.py validates and packages
  • Iterate continuously - Use on real tasks, update based on struggles

Red Flags - STOP

STOP when:

  • "Let me write all the details in SKILL.md" → Move to references (progressive disclosure)
  • "I'll use second person" → Switch to imperative voice
  • "Same information in entry and reference" → Delete duplication
  • Using generic description → Be specific about activation conditions
  • Leaving example files from init script → Delete unused resources
  • Skipping validation → Always run package_skill.py before sharing
  • Creating skill without examples → Gather concrete usage scenarios first
  • Entry point >200 lines → Apply progressive disclosure pattern

ALL of these mean: STOP. Review principles and references.

Integration with Other Skills

Meta-Skills:

  • skill-creator (this skill) - Creates other skills, demonstrates its own patterns

Development Skills:

  • mcp-builder - Example of progressive disclosure implementation
  • testing-anti-patterns - Example of ultra-lean entry point (140 lines)

Workflow Skills:

  • documentation - Writing clear, structured content
  • verification-before-completion - Testing skills before packaging

Real-World Impact

From skill optimization experience:

  • Progressive disclosure: 20-30% reduction in entry point size
  • mcp-builder: 209 → 160 lines (23% reduction, 6 references)
  • testing-anti-patterns: → 140 lines (ultra-lean with 4 references)
  • skill-creator: 209 → 150 lines (28% reduction, 5 references)
  • Context efficiency: Load only needed references (saves 50-80% context)
  • Maintainability: Update specific references without touching entry point
  • Clarity: Better organization improves discoverability and comprehension

Remember: Skills are modular packages that transform Claude into a specialized agent. Apply progressive disclosure for skills >150 lines. This skill demonstrates the pattern it teaches.

平台分布

Claude Code

30.23%
按下载量换算861

Gemini CLI

22.04%
按下载量换算628

Antigravity

16.62%
按下载量换算473

OpenCode

14.25%
按下载量换算406

windsurf

9.05%
按下载量换算258

github-copilot

3.76%
按下载量换算107

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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