langsmith-fetchlisted

# LangSmith Fetch - Agent Debugging Skill Debug LangChain and LangGraph agents by fetching execution traces directly from LangSmith Studio in your terminal. ## When to Use This Skill Automatically activate when user mentions: - 🐛 "Debug my agent" or "What went wrong?" - 🔍 "Show me recent traces" or "What happened?" - ❌ "Check for errors" or "Why did it fail?" - 💾 "Analyze memory operations" or "Check LTM" - 📊 "Review agent performance" or "Check token usage" - 🔧 "What tools were called?" or "Show execution flow" ## Prerequisites ### 1. Install langsmith-fetch ```bash pip install langsmith-fetch ``` ### 2. Set Environment Variables ```bash export LANGSMITH_API_KEY="your_langsmith_api_key" export LANGSMITH_PROJECT="your_project_name" ``` **Verify setup:** ```bash echo $LANGSMITH_API_KEY echo $LANGSMITH_PROJECT ``` ## Core Workflows ### Workflow 1: Quick Debug Recent Activity **When user asks:** "What just happened?" or "Debug my agent" **Execute:** ```bash langsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty ``` **Analyze and report:** 1. ✅ Number of traces found 2. ⚠️ Any errors or failures 3. 🛠️ Tools that were called 4. ⏱️ Execution times 5. 💰 Token usage **Example response format:** ``` Found 3 traces in the last 5 minutes: Trace 1: ✅ Success - Agent: memento - Tools: recall_memories, create_entities - Duration: 2.3s - Tokens: 1,245 Trace 2: ❌ Error - Agent: cypher - Error: "Neo4j connection timeout" - Duration: 15.1s - Failed at: search