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 5If NO traces found:
- Tracing might be disabled
- Check:
LANGCHAIN_TRACING_V2=truein environment - Check:
LANGCHAIN_API_KEYis 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-metadataAnalyze:
- 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-fetchis installed before running commands - Verify environment variables are set
- Use
--format prettyfor human-readable output - Use
--format jsonwhen 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