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fix(skills): remove phantom resource references and fix CoC links (#447)
Remove references to non-existent resource files (references/, assets/, scripts/, examples/) from 115 skill SKILL.md files. These sections pointed to directories and files that were never created, causing confusion when users install skills. Also fix broken Code of Conduct links in issue templates to use absolute GitHub URLs instead of relative paths that 404.
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@@ -632,35 +632,3 @@ index = pc.Index("my-index")
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# Create vector store with existing index
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vectorstore = PineconeVectorStore(index=index, embedding=embeddings)
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```
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## Resources
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- [LangChain Documentation](https://python.langchain.com/docs/)
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- [LangGraph Documentation](https://langchain-ai.github.io/langgraph/)
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- [LangSmith Platform](https://smith.langchain.com/)
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- [LangChain GitHub](https://github.com/langchain-ai/langchain)
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- [LangGraph GitHub](https://github.com/langchain-ai/langgraph)
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## Common Pitfalls
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1. **Using Deprecated APIs**: Use LangGraph for agents, not `initialize_agent`
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2. **Memory Overflow**: Use checkpointers with TTL for long-running agents
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3. **Poor Tool Descriptions**: Clear descriptions help LLM select correct tools
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4. **Context Window Exceeded**: Use summarization or sliding window memory
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5. **No Error Handling**: Wrap tool functions with try/except
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6. **Blocking Operations**: Use async methods (`ainvoke`, `astream`)
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7. **Missing Observability**: Always enable LangSmith tracing in production
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## Production Checklist
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- [ ] Use LangGraph StateGraph for agent orchestration
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- [ ] Implement async patterns throughout (`ainvoke`, `astream`)
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- [ ] Add production checkpointer (PostgreSQL, Redis)
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- [ ] Enable LangSmith tracing
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- [ ] Implement structured tools with Pydantic schemas
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- [ ] Add timeout limits for agent execution
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- [ ] Implement rate limiting
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- [ ] Add comprehensive error handling
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- [ ] Set up health checks
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- [ ] Version control prompts and configurations
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- [ ] Write integration tests for agent workflows
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