CCM
/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

Claude Code Marketplaces

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
  • Skill index
  • MCP index
  • Marketplace index
  • Plugins Reference

Community

  • About
  • Tools
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by mertbuilds.com

Independent project, not affiliated with Anthropic
fanthus avatar

Openclaw Expert

fanthus/agent-skills
136 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 →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
inference shell
inference shell
create and run specialised agents in minutes
build now →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
inference shell
inference shell
create and run specialised agents in minutes
build now →
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 →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
inference shell
inference shell
create and run specialised agents in minutes
build now →
Categories
Backend & APIsGit & Pull RequestsDocumentationAI & Agent BuildingDebugging
First SeenJun 3, 2026
View on GitHub

Recommended

More Backend & APIs →
samhvw8 avatar
infra-engineer

samhvw8/dotfiles

Comprehensive infrastructure engineering covering DevOps, cloud platforms, FinOps, and DevSecOps. Platforms: AWS (EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation), Azure basics, Cloudflare (Workers, R2, D1, Pages), GCP (GKE, Cloud Run, Cloud Storage), Docker, Kubernetes. Capabilities: CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), GitOps, infrastructure as code (Terraform, CloudFormation), container orchestration, cost optimization, security scanning, vulnerability management, secrets management, compliance (SOC2, HIPAA). Actions: deploy, configure, manage, scale, monitor, secure, optimize cloud infrastructure. Keywords: AWS, EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation, Azure, Kubernetes, k8s, Docker, Terraform, CI/CD, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, cost optimization, FinOps, reserved instances, spot instances, security scanning, SAST, DAST, vulnerability management, secrets management, Vault, compliance, monitoring, observability. Use when: deploying to AWS
136
14
niller2005 avatar
polymarket-trading

niller2005/polyflup

Polymarket-specific terminology, trading strategies, and API reference.
134
18
lvlup-sw avatar
design-invariants

lvlup-sw/exarchos

Audit a design proposal or diff against Exarchos's architectural invariants — event-sourcing integrity (INV-1), facade equivalence over shared dispatch core (INV-2), basileus-forward (INV-3), platform-agnosticity (INV-4), and agent-first interface design (INV-5a input ergonomics, INV-5b spec-aligned output contract, INV-5c Aspire-inspired control-plane verbs, INV-5d action discriminator pattern). Pairs with /axiom:backend-quality — this skill is project-specific (axiom is generic). Triggers: 'check invariants', 'design conformance', 'check #1118 / #1109', or /design-invariants.
132
33
zzci avatar
pma-mem

zzci/skills

Knowledge management skill for capturing, classifying, searching, and syncing project knowledge. Use when storing learnings, syncing BKD issue outcomes, or retrieving past decisions and patterns. Memos is the storage backend.
132
2
existential-birds avatar
deepagents-implementation

existential-birds/beagle

Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
131
75
garfield-bb avatar
social-media-automation

garfield-bb/hap-skills-collection

自媒体运营自动化技能,支持小红书、抖音、微信公众号、视频号等平台的内容生成、图片生成、数据管理和自动化发布。包含 Tavily API 搜索、内容生成、图片生成、HAP 数据管理和自动化发布等完整流程。新增每日热点内容推荐功能。图片生成支持并行生成、自动下载、自动跳过已存在图片等优化功能。强制要求从 HAP "账号人设" 表读取账号人设配置,禁止使用本地文件。
130
27