Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing…
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 pip install langsmith-fetch 2. Set Environment Variables export LANGSMITH_API_KEY="your_langsmith_api_key" export LANGSMITH_PROJECT="your_project_name" Verify setup: 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: langsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty Analyze and report: ✅ Number of traces found ⚠️ Any errors or failures 🛠️ Tools that were called ⏱️ Execution times 💰 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_nodes tool Trace 3: ✅ Success - Agent: memento - Tools: store_memory - Duration: 1.8s - Tokens: 892 💡 Issue found: Trace 2 failed due to Neo4j timeout. Recommend checking database connection. Workflow 2: Deep Dive Specific Trace When user provides: Trace ID or says "investigate that error" Execute: langsmith-fetch trace <trace-id> --format json Analyze JSON and report: 🎯 What the agent was trying to do 🛠️ Which tools were called (in order) ✅ Tool results (success/failure) ❌ Error messages (if any) 💡 Root cause analysis 🔧 Suggested fix Example response format: Deep Dive Analysis - Trace abc123 Goal: User asked "Find all projects in Neo4j" Execution Flow: 1. ✅ search_nodes(query: "projects") → Found 24 nodes 2. ❌ get_node_details(node_id: "proj_123") → Error: "Node not found" → This is the failure point 3. ⏹️ Execution stopped Root Cause: The search_nodes tool returned node IDs that no longer exist in the database, possibly due to recent deletions. Suggested Fix: 1. Add error handling in get_node_details tool 2. Filter deleted nodes in search results 3. Update cache invalidation strategy Token Usage: 1,842 tokens ($0.0276) Execution Time: 8.7 seconds Workflow 3: Export Debug Session When user says: "Save this session" or "Export traces" Execute: # Create session folder with timestamp SESSION_DIR="langsmith-debug/session-$(date +%Y%m%d-%H%M%S)" mkdir -p "$SESSION_DIR" # Export traces langsmith-fetch traces "$SESSION_DIR/traces" --last-n-minutes 30 --limit 50 --include-metadata # Export threads (conversations) langsmith-fetch threads "$SESSION_DIR/threads" --limit 20 Report: ✅ Session exported successfully! Location: langsmith-debug/session-20251224-143022/ - Traces: 42 files - Threads: 8 files You can now: 1. Review individual trace files 2. Share folder with team 3. Analyze with external tools 4. Archive for future reference Session size: 2.3 MB Workflow 4: Error Detection When user asks: "Show me errors" or "What's failing?" Execute: # Fetch recent traces langsmith-fetch traces --last-n-minutes 30 --limit 50 --format json > recent-traces.json # Search for errors grep -i "error\|failed\|exception" recent-traces.json Analyze and report: 📊 Total errors found ❌ Error types and frequency 🕐 When errors occurred 🎯 Which agents/tools failed 💡 Common patterns Example response format: Error Analysis - Last 30 Minutes Total Traces: 50 Failed Traces: 7 (14% failure rate) Error Breakdown: 1. Neo4j Connection Timeout (4 occurrences) - Agent: cypher - Tool: search_nodes - First occurred: 14:32 - Last occurred: 14:45 - Pattern: Happens during peak load 2. Memory Store Failed (2 occurrences) - Agent: memento - Tool: store_memory - Error: "Pinecone rate limit exceeded" - Occurred: 14:38, 14:41 3. Tool Not Found (1 occurrence) - Agent: sqlcrm - Attempted tool: "export_report" (doesn't exist) - Occurred: 14:35 💡 Recommendations: 1. Add retry logic for Neo4j timeouts 2. Implement rate limiting for Pinecone 3. Fix sqlcrm tool configuration Common Use Cases Use Case 1: "Agent Not Responding" User says: "My agent isn't doing anything" Steps: Check if traces exist: langsmith-fetch traces --last-n-minutes 5 --limit 5 If NO traces found: Tracing might be disabled Check: LANGCHAIN_TRACING_V2=true in environment Check: LANGCHAIN_API_KEY is set Verify agent actually ran If traces found: Review for errors Check execution time (hanging?) Verify tool calls completed Use Case 2: "Wrong Tool Called" User says: "Why did it use the wrong tool?" Steps: Get the specific trace Review available tools at execution time Check agent's reasoning for tool selection Examine tool descriptions/instructions Suggest prompt or tool config improvements Use Case 3: "Memory Not Working" User says: "Agent doesn't remember things" Steps: Search for memory operations: langsmith-fetch traces --last-n-minutes 10 --limit 20 --format raw | grep -i "memory\|recall\|store" Check: Were memory tools called? Did recall return results? Were memories actually stored? Are retrieved memories being used? Use Case 4: "Performance Issues" User says: "Agent is too slow" Steps: Export with metadata: langsmith-fetch traces ./perf-analysis --last-n-minutes 30 --limit 50 --include-metadata Analyze: Execution time per trace Tool call latencies Token usage (context size) Number of iterations Slowest operations Identify bottlenecks and suggest optimizations Output Format Guide Pretty Format (Default) langsmith-fetch traces --limit 5 --format pretty Use for: Quick visual inspection, showing to users JSON Format langsmith-fetch traces --limit 5 --format json Use for: Detailed analysis, syntax-highlighted review Raw Format langsmith-fetch traces --limit 5 --format raw Use for: Piping to other commands, automation Advanced Features Time-Based Filtering # After specific timestamp langsmith-fetch traces --after "2025-12-24T13:00:00Z" --limit 20 # Last N minutes (most common) langsmith-fetch traces --last-n-minutes 60 --limit 100 Include Metadata # Get extra context langsmith-fetch traces --limit 10 --include-metadata # Metadata includes: agent type, model, tags, environment Concurrent Fetching (Faster) # Speed up large exports langsmith-fetch traces ./output --limit 100 --concurrent 10 Troubleshooting "No traces found matching criteria" Possible causes: No agent activity in the timeframe Tracing is disabled Wrong project name API key issues Solutions: # 1. Try longer timeframe langsmith-fetch traces --last-n-minutes 1440 --limit 50 # 2. Check environment echo $LANGSMITH_API_KEY echo $LANGSMITH_PROJECT # 3. Try fetching threads instead langsmith-fetch threads --limit 10 # 4. Verify tracing is enabled in your code # Check for: LANGCHAIN_TRACING_V2=true "Project not found" Solution: # View current config langsmith-fetch config show # Set correct project export LANGSMITH_PROJECT="correct-project-name" # Or configure permanently langsmith-fetch config set project "your-project-name" Environment variables not persisting Solution: # Add to shell config file (~/.bashrc or ~/.zshrc) echo 'export LANGSMITH_API_KEY="your_key"' >> ~/.bashrc echo 'export LANGSMITH_PROJECT="your_project"' >> ~/.bashrc # Reload shell config source ~/.bashrc Best Practices 1. Regular Health Checks # Quick check after making changes langsmith-fetch traces --last-n-minutes 5 --limit 5 2. Organized Storage langsmith-debug/ ├── sessions/ │ ├── 2025-12-24/ │ └── 2025-12-25/ ├── error-cases/ └── performance-tests/ 3. Document Findings When you find bugs: Export the problematic trace Save to error-cases/ folder Note what went wrong in a README Share trace ID with team 4. Integration with Development # Before committing code langsmith-fetch traces --last-n-minutes 10 --limit 5 # If errors found langsmith-fetch trace <error-id> --format json > pre-commit-error.json Quick Reference # Most common commands # Quick debug langsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty # Specific trace langsmith-fetch trace <trace-id> --format pretty # Export session langsmith-fetch traces ./debug-session --last-n-minutes 30 --limit 50 # Find errors langsmith-fetch traces --last-n-minutes 30 --limit 50 --format raw | grep -i error # With metadata langsmith-fetch traces --limit 10 --include-metadata Resources LangSmith Fetch CLI: https://github.com/langchain-ai/langsmith-fetch LangSmith Studio: https://smith.langchain.com/ LangChain Docs: https://docs.langchain.com/ This Skill Repo: https://github.com/OthmanAdi/langsmith-fetch-skill Notes for Claude Always check if langsmith-fetch is installed before running commands Verify environment variables are set Use --format pretty for human-readable output Use --format json when you need to parse and analyze data When exporting sessions, create organized folder structures Always provide clear analysis and actionable insights If commands fail, help troubleshoot configuration issues Version: 0.1.0 Author: Ahmad Othman Ammar Adi License: MIT Repository: https://github.com/OthmanAdi/langsmith-fetch-skill
don't have the plugin yet? install it then click "run inline in claude" again.