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skill-creator技能创建器

Agent Skill

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。

总安装

192

周安装

8

GitHub Stars

7

下载量

64
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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/ingpoc/skills
仓库路径:skills/skill-creator
安装命令:
npx skills add https://github.com/ingpoc/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/ingpoc/skills --skill skill-creator

简介

用于查找、检索和筛选相关信息,适合根据关键词快速定位候选结果。

  • 可结合任务场景或来源线索进行信息聚合,支持技能库探索和匹配。
  • 安装前建议确认权限范围和维护状态,避免触发不必要的联网或文件操作。
  • 安装命令为 npx skills add https://github.com/ingpoc/skills --skill skill-creator。
  • 适用于 Codex、Claude、Cursor、Gemini CLI,需通过 GitHub 仓库安装。

SKILL.md

Skill Creator

Create modular, token-efficient skills that extend Claude's capabilities.

Critical: Description = Trigger

The description field in frontmatter is how Claude decides when to load a skill.

LocationClaude SeesTiming
description (frontmatter)Always in contextBefore trigger
"When to Use" (body)Only after triggeredToo late!

Pattern:

---
name: pdf-toolkit
# GOOD - trigger info in description
description: "Use when processing PDFs, extracting forms, merging documents, or filling PDF forms. Load for any PDF manipulation task."
keywords: pdf, extract, merge, forms
---

Anti-pattern:

---
name: pdf-toolkit
# BAD - trigger info only in body (Claude can't see until AFTER trigger)
description: "PDF manipulation toolkit"
---

## When to Use  ← Claude never sees this before deciding to trigger!

Skill Anatomy

skill-name/
├── SKILL.md (required)      # Workflow + metadata (<5k words)
├── scripts/ (optional)      # Executable code (0 tokens when run)
├── references/ (optional)   # Docs loaded as needed
└── assets/ (optional)       # Output resources (never loaded)

Resource Types

TypeWhen to UseToken CostExamples
scripts/Repeated code, deterministic0 (executes)rotate_pdf.py, validate.sh
references/Schemas, APIs, patternsOn-demandschema.md, api_docs.md
assets/Templates, images0 (output only)logo.png, template.docx

Key insight: Scripts execute WITHOUT loading into context = 0 tokens.

Progressive Disclosure (3 Levels)

LevelWhatWhen LoadedToken Budget
1. Metadataname + descriptionAlways~100 words
2. SKILL.md bodyInstructionsOn trigger<5k words
3. Resourcesscripts/references/assetsAs neededUnlimited

Result: 98% token savings vs loading everything upfront.

Skill Creation Workflow

1. Gather Examples

Ask user:

  • What functionality should the skill support?
  • Example usage scenarios?
  • What triggers this skill?

2. Plan Resources

QuestionMaps To
What code gets rewritten?scripts/
What schemas get rediscovered?references/
What boilerplate gets recreated?assets/

3. Initialize

scripts/init_skill.py <skill-name> --path <output-directory>

4. Write SKILL.md

Order:

  1. Write description (with ALL trigger scenarios)
  2. Add keywords
  3. Write concise body (<5k words)
  4. Reference bundled resources

Frontmatter checklist:

  • name: lowercase, hyphens
  • description: starts with "Use when...", includes ALL triggers
  • keywords: discovery tags

Body checklist:

  • Instructions (imperative form)
  • Resource table (what to load when)
  • Quick reference (common commands)

5. Validate & Package

scripts/quick_validate.py <path/to/skill>
scripts/package_skill.py <path/to/skill> [output-dir]

6. Iterate

Test on real tasks → identify gaps → update → test again.

Key Rules

RuleWhy
Description = triggerClaude decides from metadata, not body
Scripts = 0 tokensExecute without loading into context
Tables over prose30-50% token savings
<5k words in SKILL.mdMove details to references/
keywords for discoveryHelps Claude find relevant skills

References

FileLoad When
references/best_practices.mdWriting style, organization
references/progressive_disclosure.mdToken efficiency patterns
references/examples.mdSkill structure examples

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Antigravity

30.21%
按下载量换算19

windsurf

21.07%
按下载量换算13

OpenCode

15.9%
按下载量换算10

Codex

13.72%
按下载量换算9

Claude Code

7.96%
按下载量换算5

Gemini CLI

3.68%
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

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

来源信息

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