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clawhub-skill-creatorClawHub 技能 creator

Agent Skill

clawhub-skill-creator 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

19,310

周安装

821

GitHub Stars

2

下载量

6,765
OpenClaw

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

2

许可证

MIT-0

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:clawhub-skill-creator(ClawHub 技能 creator)
来源仓库:https://github.com/erview/clawhub-skill-creator
安装命令:
openclaw skills install clawhub-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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install clawhub-skill-creator

简介

创建和更新clawhub注册表的技能;优化结构、验证元数据并确保 AI 代理使用的兼容性。

SKILL.md

name
clawhub-skill-creator
description
Create effective skills for clawhub registry. Use when: (1) Creating new skill for publication, (2) Updating existing skill metadata, (3) Optimizing skill structure for AI agents, (4) Validating skill before publish, (5) Understanding clawhub-specific requirements.

Clawhub Skill Creator

Complete guide for creating skills compatible with clawhub registry and optimized for AI agent usage.

Language Rule

Skill description must be in English, unless context requires otherwise (examples, comments, etc. may use other languages when appropriate).

  • description in frontmatter: English only
  • SKILL.md body: English preferred
  • Examples, code comments: Any language as needed
  • References: Any language as appropriate for domain

Quick Start

Create New Skill

# Run initializer
./scripts/init-skill.sh my-skill

# Or manually create structure
mkdir -p my-skill/{references,scripts,assets}
touch my-skill/SKILL.md my-skill/_meta.json my-skill/LICENSE.txt

Skill Creation Workflow

Phase 1: Understand Requirements

Before writing any code, clarify:

  1. What problem does this skill solve?

- Concrete use cases (2-3 examples) - Target queries that should trigger skill

  1. Who will use this skill?

- AI agents (primary audience for clawhub) - Expected context (tools available, environment)

  1. What resources are needed?

- References for detailed docs? - Assets for templates? - Scripts for automation?

Output: Clear understanding of skill scope and triggers.

Phase 2: Plan Structure

Choose pattern based on complexity:

ComplexityStructureWhen to Use
SimpleSKILL.md only<100 lines, single purpose
Medium+ references/100-300 lines, some details
Complex+ references/ + assets/>300 lines, multi-domain

Decide on resources:

  • Which references needed? (docs, examples, patterns)
  • Which assets needed? (templates, configs)
  • Which scripts needed? (validation, packaging)

Output: Directory structure and resource list.

Phase 3: Initialize Structure

# Create directory
mkdir -p my-skill/{references,scripts,assets}

# Create required files
touch my-skill/SKILL.md
touch my-skill/_meta.json
touch my-skill/LICENSE.txt

Required files for clawhub:

my-skill/
├── SKILL.md              # Instructions and metadata (required)
├── _meta.json            # Registry metadata (required)
├── LICENSE.txt           # License file (required)
├── references/           # Optional: detailed documentation
├── scripts/              # Optional: automation scripts
└── assets/               # Optional: templates, resources

Phase 4: Write SKILL.md

Frontmatter (YAML)

---
name: skill-name
description: What it does. Use when: (1) trigger-1, (2) trigger-2, (3) trigger-3.
---

Critical rules:

  • name must match directory name
  • description is ONLY trigger mechanism — include all "when to use" here
  • description must be in English
  • Only name and description are required in frontmatter

Body Structure

# Skill Title

Brief purpose (1-2 sentences).

## Quick Start

**Linux/Mac:**

command --option


**Windows CMD:**

command --option


**PowerShell:**

command --option


## When to Use

- Situation 1: What to do
- Situation 2: What to do
- Situation 3: What to do

## Workflow

1. **Step one**: Description
2. **Step two**: Description
3. **Step three**: Description

## Resources

- `references/advanced.md` - For complex cases
- `references/examples.md` - Usage examples
- `assets/template.txt` - Starting template

Writing guidelines:

  • Imperative voice ("Open file", not "You should open file")
  • Concrete examples over abstract explanations
  • Platform-aware commands
  • Navigation to references
  • English preferred for body text

Phase 5: Create _meta.json

{
  "name": "skill-name",
  "version": "1.0.0",
  "description": "Short description for registry listing",
  "requires": {
    "env": ["ENV_VAR_1", "ENV_VAR_2"],
    "credentials": ["credential_name"]
  },
  "tags": ["tag1", "tag2", "latest"]
}

Fields explained:

  • name: Must match directory and SKILL.md frontmatter
  • version: Semver (X.Y.Z), check registry before setting
  • description: For registry listing, must be in English
  • requires.env: Environment variables needed
  • requires.credentials: Credentials needed
  • tags: Include "latest" for discoverability

Phase 6: Add LICENSE.txt

Choose license (MIT recommended):

MIT License

Copyright (c) 2025 [Author]

Permission is hereby granted...

Phase 7: Write References (if needed)

Create files in references/:

# Reference Title

Detailed documentation here.

## Section

Content...

Guidelines:

  • One topic per file
  • <5K words per file
  • Link from SKILL.md with clear context
  • No deeply nested references
  • Language: English preferred, domain-specific allowed

Phase 8: Validate Locally

# Check structure
./scripts/validate.sh my-skill

# Or manual checks:
# - SKILL.md exists and has frontmatter
# - _meta.json is valid JSON
# - LICENSE.txt exists
# - No README.md, CHANGELOG.md
# - Line count < 300
# - References linked correctly

Validation checklist:

  • [ ] Directory name matches name in frontmatter and _meta.json
  • [ ] description in English, includes "Use when:" triggers
  • [ ] SKILL.md < 300 lines
  • [ ] _meta.json valid JSON
  • [ ] No extraneous files (README, CHANGELOG)
  • [ ] References exist and linked
  • [ ] Token estimate < 10K

Phase 9: Test with Agent

Trigger test:

  • Does skill activate for intended queries?
  • Does description correctly trigger skill?

Workflow test:

  • Can agent follow steps without clarification?
  • Are commands clear and executable?

Resource test:

  • Are references loaded at appropriate time?
  • Is navigation clear?

Edge case test:

  • How does skill handle errors?
  • Are platform differences handled?

Phase 10: Iterate (if needed)

If tests reveal issues:

  1. Identify problem

- Trigger not working? → Fix description - Workflow unclear? → Rewrite steps - Missing info? → Add reference

  1. Update files

- SKILL.md, _meta.json, or references

  1. Re-validate and re-test

- Go back to Phase 8

  1. Repeat until satisfied

Iterate cycle: Phase 8 → Phase 9 → Phase 10 (loop) → Phase 11

Phase 11: Check Version

Before publishing, verify current registry version:

# Check current registry version
clawhub inspect skill-name --json | grep version

# Ensure new version follows semver:
# 1.0.0 → 1.0.1 (patch: bug fixes)
# 1.0.0 → 1.1.0 (minor: new features)
# 1.0.0 → 2.0.0 (major: breaking changes)

# Never downgrade! (1.1.0 → 1.0.2 is wrong)

Update _meta.json with correct version:

{
  "version": "1.0.1"
}

Phase 12: Package

# Create .skill package for distribution
./scripts/package-skill.sh my-skill ./dist

# Output: dist/my-skill.skill
# Validates structure before packaging

Package contains:

  • All skill files
  • Validated structure
  • Ready for distribution

Phase 13: Publish

cd my-skill

# Publish to clawhub
clawhub publish . --version 1.0.1 --changelog "Description of changes"

# Verify publication
clawhub inspect skill-name

After publish:

  • Skill available in registry
  • Others can install via clawhub install skill-name

Required Files for Clawhub

SKILL.md

Instructions and metadata:

  • YAML frontmatter (name, description in English)
  • Markdown body (workflow, examples)
  • Navigation to references

_meta.json

Registry metadata:

{
  "name": "skill-name",
  "version": "1.0.0",
  "description": "Registry listing description in English",
  "requires": {
    "env": [],
    "credentials": []
  },
  "tags": ["latest"]
}

LICENSE.txt

License file (MIT, Apache-2.0, etc.)

Resources

  • references/skill-structure.md - Directory structure patterns
  • references/agent-first-design.md - Designing for AI vs humans
  • references/token-optimization.md - Minimizing context usage
  • references/cross-platform.md - Platform-aware scripts
  • references/validation-checklist.md - Pre-publish checks
  • references/versioning.md - Semver best practices

Key Principles

1. Agent-First Design

Skills used by AI agents, not humans:

  • ❌ No interactive prompts
  • ❌ No platform-specific scripts (use knowledge instead)
  • ✅ Command templates for all platforms
  • ✅ Clear navigation to references

2. Progressive Disclosure

Level 1: Metadata (name + description)     → Always loaded
Level 2: SKILL.md body                      → On trigger
Level 3: Resources (references/, assets/)   → On demand

3. Token Budget

ComponentTargetMax
Metadata50 words100 words
SKILL.md200 lines300 lines
References3K words5K words
Total5K tokens10K tokens

4. Cross-Platform Awareness

Instead of script:

## Commands

**Linux/Mac:**

command --option


**Windows CMD:**

command --option


**PowerShell:**

command --option

Agent chooses appropriate variant based on detected platform.

5. English Language for Descriptions

Required in English:

  • description in SKILL.md frontmatter
  • description in _meta.json
  • Main workflow instructions

May use other languages:

  • Code examples
  • Comments
  • Domain-specific references
  • User-facing examples

Scripts

  • scripts/init-skill.sh - Initialize new skill structure
  • scripts/package-skill.sh - Package skill for distribution
  • scripts/validate.sh - Validate skill structure

Anti-Patterns

Don't:

  • Put "When to use" only in body (must be in description)
  • Use non-English description in frontmatter
  • Duplicate info between SKILL.md and references
  • Create README.md, CHANGELOG.md (clutter)
  • Use platform-specific scripts (sh/bat)
  • Write passive voice ("You should")
  • Include generic background theory
  • Skip validation before publish
  • Forget to bump version
  • Publish without testing

Do:

  • Write description in English
  • Start with concrete examples
  • Move details to references/
  • Use imperative voice ("Do X")
  • Challenge every sentence's value
  • Test with real agent queries
  • Validate before publish
  • Follow semver strictly
  • Iterate based on test results

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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

OpenClaw

88.62%
按下载量换算5,995

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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