CAT
/Skills
SkillsMCPMarketplacesDigestToolsAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Cross AI Tools

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Plugins Reference

Community

  • About
  • Tools
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

Openclaw Expert

fanthus/agent-skills
131 installs
Summary

This pulls fresh documentation from OpenClaw's official docs and GitHub repo whenever you ask a question, then synthesizes actual answers with source links. It's built around the reality that framework docs change constantly, so instead of relying on stale knowledge, it fetches the current pages for installation, API usage, configuration, or whatever you're asking about. The workflow categorizes your question, grabs the right docs pages, and formats responses with code examples and URLs. Useful when you're working with OpenClaw and need accurate answers that cite their sources rather than hallucinated guesses about how something works.

Install to Claude Code

npx -y skills add fanthus/agent-skills --skill openclaw-expert --agent claude-code

Installs into .claude/skills of the current project.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Files
SKILL.mdView on GitHub

OpenClaw Learning Expert

This skill helps answer questions about OpenClaw by retrieving information from official documentation and the GitHub repository, then providing comprehensive answers with source links.

Workflow

When the user asks an OpenClaw-related question:

Step 1: Identify the Question Type

Categorize the question to determine the best sources:

  • Getting Started/Installation → Documentation: /start/getting-started
  • Concepts/Architecture → Documentation: /concepts/ sections
  • API Usage → Documentation: /api/ + GitHub examples
  • Configuration → Documentation: /guides/configuration
  • Troubleshooting → GitHub Issues + Documentation
  • Examples/Implementations → GitHub /examples directory
  • Advanced/Source Code → GitHub repository source code

Step 2: Fetch Relevant Documentation

Use web_fetch tool to retrieve content from:

  1. Primary source: Official documentation at https://docs.openclaw.ai/

    • Start with the most relevant documentation page based on the question type
    • Common pages: /start/getting-started, /concepts/, /api/, /guides/
  2. Secondary source: GitHub repository at https://github.com/openclaw/openclaw

    • For code examples, implementation details, or when docs need clarification
    • Check README.md, examples directory, or source code as needed

Important: Always fetch the actual pages rather than guessing content, as OpenClaw is actively developed and documentation changes frequently.

Step 3: Synthesize Information

After retrieving documentation:

  1. Extract relevant information that answers the user's question
  2. Organize the answer in a clear, logical structure:
    • Start with a direct answer to the question
    • Provide necessary context or explanation
    • Include code examples if relevant
    • Note any caveats or best practices
  3. Cite sources by including the specific documentation URLs used

Step 4: Present the Answer

Format the response as follows:

[Direct answer to the question]

[Explanation and details]

[Code examples if applicable]

**Sources:**
- [Specific page title]: [Full URL to the documentation page]
- [Another source if used]: [Full URL]

Example response structure:

OpenClaw uses a declarative configuration approach for defining workflows.

To configure a workflow, you create a YAML file that specifies...

Example:
```yaml
workflow:
  name: example
  steps:
    - action: process

Sources:

  • Getting Started Guide: https://docs.openclaw.ai/start/getting-started
  • Configuration Reference: https://docs.openclaw.ai/guides/configuration

## Best Practices

1. **Always fetch current documentation** - Don't rely on cached knowledge
2. **Provide specific URLs** - Include the exact page where information was found
3. **Include code examples** - When available in the documentation, include them
4. **Be comprehensive** - Cover edge cases and common pitfalls mentioned in docs
5. **Link to GitHub for implementation** - When users need to see source code or examples
6. **Check multiple sources** - If documentation is unclear, cross-reference with GitHub
7. **Note version information** - If the documentation mentions specific versions, include that context

## Handling Common Scenarios

### Question Not Directly Answered in Docs

1. Search GitHub Issues for similar questions
2. Check GitHub Discussions
3. Examine source code or examples for implementation patterns
4. Provide best available information with caveats

### Multiple Possible Answers

1. Present all relevant approaches found in documentation
2. Note recommended approach if docs specify one
3. Explain trade-offs when applicable

### Outdated or Conflicting Information

1. Prioritize official documentation over GitHub README
2. Note any conflicts found between sources
3. Suggest checking GitHub Issues for latest updates
4. Provide the most recent information available

## Reference Files

- **references/documentation_guide.md** - Overview of documentation structure and search strategies (consult when unsure where to find specific information)

## Tools to Use

- **web_fetch** - Primary tool for retrieving documentation pages
- **web_search** - For finding specific pages or GitHub issues when exact URL is unknown

## Notes

- OpenClaw is actively developed - always fetch fresh documentation
- User's questions may be in Chinese or English - respond in the same language
- Include both Chinese and English technical terms when appropriate
- Always verify URLs work before including in response
Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Categories
AI & Agent Building
First SeenJun 3, 2026
View on GitHub

Recommended

More AI & Agent Building →
agent-memory-mcp

sickn33/antigravity-awesome-skills

agent memory mcp
954
39.4k
agent-memory-mcp

davila7/claude-code-templates

agent memory mcp
521
27.7k
llm-application-dev-langchain-agent

sickn33/antigravity-awesome-skills

llm application dev langchain agent
306
39.4k
llm-application-dev

moizibnyousaf/ai-agent-skills

Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
1.1k
ai-prompt-engineering-safety-review

github/awesome-copilot

Comprehensive safety analysis and improvement framework for AI prompts with detailed assessment methodologies.
9.4k
34.3k
emblem-ai-prompt-examples

emblemcompany/agent-skills

emblem ai prompt examples
8.7k
10