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Agent Skill · 研究检索

creating-skills(创造技能)

creating-skills 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。

creating-skills 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 73,675 个 Skill 里排第 67,317。

总安装 247周安装 10GitHub Stars 24下载 78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:creating-skills(创造技能)
来源仓库:https://github.com/sawyer-middeleer/dot-claude
仓库路径:skills/creating-skills
安装命令:
npx skills add https://github.com/sawyer-middeleer/dot-claude --skill creating-skills
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/sawyer-middeleer/dot-claude --skill creating-skills

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。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位结果。适合在需要根据线索快速获取候选信息时使用。可结合来源仓库与原始 README 进一步验证具体功能与使用方式。安装通过 GitHub,适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境。

使用前应确认权限范围、维护状态,避免触发联网、命令执行或文件读写操作。

来源仓库内路径:skills/creating-skills

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/sawyer-middeleer/dot-claude --skill creating-s…;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

creating-skills 怎么安装?

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

creating-skills 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。

creating-skills 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。

creating-skills 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。

creating-skills 用的人多吗?

公开数据是累计安装 247 次,近一周安装 10 次,下载 78 次,GitHub 24 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。

creating-skills 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
creating-skills

创造技能 · 本页

24724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

Creating High-Quality Claude Skills

Use this skill when creating or improving Claude skills to ensure they follow official best practices and work effectively across all Claude models.

Core Principles

Conciseness: Skills share the context window. Only include information Claude doesn't already have.

Appropriate Freedom: Match instruction detail to task needs:

  • High freedom: Multiple valid approaches (use text instructions)
  • Medium freedom: Preferred patterns with flexibility (use pseudocode/guidance)
  • Low freedom: Exact sequences required (use specific bash/python scripts)

Progressive Disclosure: Keep SKILL.md under 500 lines. Split content into reference files when approaching this limit. All references must be one level deep.

Phase 1: Initial Clarification (CRITICAL)

BEFORE planning or writing the skill, use the AskUserQuestion tool to gather structured feedback on skill requirements.

Ask the user to clarify (only if needed):

  1. Instruction detail level: How much freedom should Claude have? (use AskUserQuestion with single select)

- High freedom - Multiple valid approaches, text instructions only - Medium freedom - Preferred patterns with flexibility, pseudocode/guidance - Low freedom - Exact sequences required, specific scripts

  1. Success criteria: How will success be measured? Suggest options contextually based on skill type. (use AskUserQuestion with multiSelect: true)
  2. Special considerations: Are there any special requirements? Suggest options contextually based on skill type. (use AskUserQuestion with multiSelect: true)

Feel free to include 1-2 additional multiSelect questions if it's essential to clarify workflow steps, inputs and outputs, or other materials to include in the skill. You can write the questions and answer options based on context if you want to do this.

Phase 2: Design & Planning

After gathering requirements in Phase 1, design the skill structure:

  1. Choose skill name

- Use gerund form (verb + -ing, max 64 chars) - Lowercase letters, numbers, hyphens only - Avoid: helper, utils, or words containing "anthropic"/"claude" as these are reserved words

  1. Write description

- Include specific keywords for discovery - State what the skill does and when to use it - Keep under 1024 chars, write in third person

  1. Plan content structure

- Determine if single file (< 400 lines) or progressive disclosure needed - Identify sections: workflow, examples, templates, validation - Note which parts need high/medium/low freedom based on Phase 1

  1. Generate architecture diagram

- Create ASCII architecture diagram showing full skill structure - Follow the format guidelines in reference/architecture-diagrams.md - Include: phases, components, decision trees, file structure, validation flows

  1. Present plan to user

- Share proposed name, description, and structure outline - Present the architecture diagram for visual validation - Confirm alignment with their expectations - Adjust based on feedback before proceeding to implementation

Phase 3: Create Content

  1. Write SKILL.md

- Add valid YAML frontmatter - Include only information Claude doesn't already have - Add workflows with checklists for complex tasks

  1. Add supplementary files (if needed)

- Create subdirectory(ies) (e.g., examples/, templates/, scripts/, etc) - Split content into focused topics (one level deep only) - Ensure SKILL.md remains under 500 lines

  1. Implement feedback mechanisms (if identified in Phase 1)

- Add validation checkpoints - Structure quality review loops - Specify error handling approaches

Phase 4: Validate Quality

Before finalizing, run through the quality checklist:

  • Valid YAML frontmatter with name and description
  • Name follows conventions (gerund, ≤64 chars, lowercase/hyphens)
  • Description includes usage triggers (≤1024 chars)
  • SKILL.md under 500 lines
  • Supporting files (if any) are one level deep
  • Only includes information Claude doesn't already have
  • Consistent terminology throughout
  • Concrete examples provided
  • Scripts (if any) have explicit error handling
  • File paths use forward slashes
  • Dependencies documented

YAML Frontmatter (Required)

Every skill must start with:

---
name: skill-name-here
description: Clear description with keywords, functionality, and usage triggers for discovery.
---

Name requirements:

  • Lowercase letters, numbers, hyphens only (max 64 chars)
  • Use gerund form: processing-pdfs, analyzing-spreadsheets
  • Avoid: helper, utils, or words containing "anthropic"/"claude"

Description requirements:

  • Non-empty, no XML tags (max 1024 chars)
  • Write in third person
  • Include specific keywords and when to use this skill
  • Think: "How will this be found among 100+ skills?"

Content Organization

Single File vs. Progressive Disclosure

Use single SKILL.md when:

  • Content is under 400 lines
  • Information is tightly related
  • Users need everything at once

Use progressive disclosure when:

  • Approaching 500 lines
  • Content has distinct topics
  • Some details are conditional/advanced

Progressive disclosure patterns:

SKILL.md (overview + core workflow)
└── reference/
    ├── topic-one.md
    ├── topic-two.md
    └── advanced-features.md

Critical rule: Never nest references. All reference files must be directly under a single subdirectory.

Content Principles

Core principles for writing effective skill content: conciseness, freedom levels, and progressive disclosure.

Conciseness

Skills share the context window with conversation history and other skills. Every word must earn its place.

Challenge Every Detail

Before including any information, ask:

  • Is this essential for the task?
  • Could this be inferred from context?
  • Does this duplicate instruction that already exists?

Example - Essential information only:

## Processing CSV Files

When processing CSVs:
1. Validate column headers match expected schema
2. Check for encoding issues (default to UTF-8)
3. Handle missing values explicitly (null vs. empty string)

Focus on Unique Information

Only include what Claude doesn't already know or what's specific to your use case:

Example (unique, actionable information):

## Data Processing Requirements

For this workflow, use pandas with these constraints:
- Preserve original column order (df.reindex())
- Handle timestamps in Pacific timezone
- Round currency values to 2 decimal places

Remove Redundant Explanations

Don't explain the same concept multiple times:

Example:

## Workflow

1. **Validate Input**: Check schema and data types
2. **Process Data**: Apply transformations
3. **Generate Output**: Format and export results

Common Content Patterns

Workflows with Checklists

Break complex tasks into steps:

1. **Analyze Input**
   - [ ] Validate format
   - [ ] Check required fields
   - [ ] Identify issues

2. **Process Data**
   - [ ] Apply transformations
   - [ ] Handle edge cases
   - [ ] Validate output

Templates and Examples

Provide concrete demonstrations:

## Example: API Request

\`\`\`python
# Use this pattern for all API calls
response = requests.post(
    url="https://api.example.com/endpoint",  # API endpoint
    json={"key": "value"},  # Request payload
    timeout=30  # Prevent hanging (API rate limits)
)
\`\`\`

Feedback Loops

Implement validation cycles:

1. Run validation
2. If errors found → review → fix → return to step 1
3. If passes → proceed

Scripts and Code Guidelines

Error handling: Scripts should provide specific, actionable messages

if df['date'].isna().any():
    missing_count = df['date'].isna().sum()
    print(f"Error: {missing_count} rows have missing dates.")
    print(f"Affected rows: {df[df['date'].isna()].index.tolist()}")
    print("Solution: Remove rows or fill with interpolated values.")

File paths: Always use forward slashes for cross-platform compatibility

  • ✓ data/input/file.csv
  • ✗ data\input\file.csv

Dependencies: Document required packages and explain configuration values

MCP tools: Use fully qualified names: ServerName:tool_name

See reference/scripts-and-code.md for comprehensive guidance.

Quality Checklist (Essential)

Before finalizing a skill:

Structure:

  • Valid YAML frontmatter with name and description
  • Name follows conventions (gerund, ≤64 chars, lowercase/hyphens)
  • Description includes usage triggers (≤1024 chars)
  • SKILL.md under 500 lines
  • Reference files (if any) are one level deep

Content:

  • Consistent terminology throughout
  • Concrete examples provided
  • Workflows use checkboxes for complex tasks
  • No time-sensitive information

Technical:

  • Scripts have explicit error handling
  • File paths use forward slashes
  • Dependencies documented
  • No "magic numbers" (all config explained)

Reference Files

For detailed guidance on specific topics:

平台分布

Claude Code

26.96%
按下载量换算21

windsurf

22.38%
按下载量换算17

trae

18.1%
按下载量换算14

OpenCode

12.79%
按下载量换算10

Cursor

7.88%
按下载量换算6

Codex

2.96%
按下载量换算2

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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