Use this skill for ANY LangSmith/LangChain observability question. Covers two topics: (1) Adding tracing to your application (LangChain/LangGraph or vanilla Python/TS with @traceable), and (2) Querying traces for debugging, analyzing execution flow, and exporting trace data.
Quickly install langsmith-trace AI skill to your development environment via command line
Source: jackjin1997/clawforge.
Two main topics: adding tracing to your application, and querying traces for debugging and analysis.
Check the codebase first: If using OpenTelemetry, prefer the OTel integration (https://docs.langchain.com/langsmith/trace-with-opentelemetry). For Vercel AI SDK, LlamaIndex, Instructor, DSPy, or LiteLLM, see native integrations at https://docs.langchain.com/langsmith/integrations.
If not using an integration, use the @traceable decorator and wrap your LLM client:
Use this skill for ANY LangSmith/LangChain observability question. Covers two topics: (1) Adding tracing to your application (LangChain/LangGraph or vanilla Python/TS with @traceable), and (2) Querying traces for debugging, analyzing execution flow, and exporting trace data. Source: jackjin1997/clawforge.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/jackjin1997/clawforge --skill langsmith-traceUse this skill for ANY LangSmith/LangChain observability question. Covers two topics: (1) Adding tracing to your application (LangChain/LangGraph or vanilla Python/TS with @traceable), and (2) Querying traces for debugging, analyzing execution flow, and exporting trace data. Source: jackjin1997/clawforge.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/jackjin1997/clawforge --skill langsmith-trace Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/jackjin1997/clawforge