Langsmith Fetch

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_KEYecho $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:

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_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:

1. 🎯 What the agent was trying to do
2. 🛠️ Which tools were called (in order)
3. ✅ Tool results (success/failure)
4. ❌ Error messages (if any)
5. 💡 Root cause analysis
6. 🔧 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 tool2. Filter deleted nodes in search results3. 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 timestampSESSION_DIR="langsmith-debug/session-$(date +%Y%m%d-%H%M%S)"mkdir -p "$SESSION_DIR"
# Export traceslangsmith-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 files2. Share folder with team3. Analyze with external tools4. 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 traceslangsmith-fetch traces --last-n-minutes 30 --limit 50 --format json > recent-traces.json
# Search for errorsgrep -i "error\|failed\|exception" recent-traces.json

Analyze and report:

1. 📊 Total errors found
2. ❌ Error types and frequency
3. 🕐 When errors occurred
4. 🎯 Which agents/tools failed
5. 💡 Common patterns

Example response format:

Error Analysis - Last 30 Minutes
Total Traces: 50Failed 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 timeouts2. Implement rate limiting for Pinecone3. Fix sqlcrm tool configuration

Common Use Cases

Use Case 1: "Agent Not Responding"

User says: "My agent isn't doing anything"

Steps:

1. Check if traces exist:

   bash

   langsmith-fetch traces --last-n-minutes 5 --limit 5

2. 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

3. 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:

1. Get the specific trace
2. Review available tools at execution time
3. Check agent's reasoning for tool selection
4. Examine tool descriptions/instructions
5. Suggest prompt or tool config improvements

Use Case 3: "Memory Not Working"

User says: "Agent doesn't remember things"

Steps:

1. Search for memory operations:

   bash

   langsmith-fetch traces --last-n-minutes 10 --limit 20 --format raw | grep -i "memory\|recall\|store"

2. 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:

1. Export with metadata:

   bash

   langsmith-fetch traces ./perf-analysis --last-n-minutes 30 --limit 50 --include-metadata

2. Analyze:

   • Execution time per trace
   • Tool call latencies
   • Token usage (context size)
   • Number of iterations
   • Slowest operations

3. 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 timestamplangsmith-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 contextlangsmith-fetch traces --limit 10 --include-metadata
# Metadata includes: agent type, model, tags, environment

Concurrent Fetching (Faster)

# Speed up large exportslangsmith-fetch traces ./output --limit 100 --concurrent 10

Troubleshooting

"No traces found matching criteria"

Possible causes:

1. No agent activity in the timeframe
2. Tracing is disabled
3. Wrong project name
4. API key issues

Solutions:

# 1. Try longer timeframelangsmith-fetch traces --last-n-minutes 1440 --limit 50
# 2. Check environmentecho $LANGSMITH_API_KEYecho $LANGSMITH_PROJECT
# 3. Try fetching threads insteadlangsmith-fetch threads --limit 10
# 4. Verify tracing is enabled in your code# Check for: LANGCHAIN_TRACING_V2=true

"Project not found"

Solution:

# View current configlangsmith-fetch config show
# Set correct projectexport LANGSMITH_PROJECT="correct-project-name"
# Or configure permanentlylangsmith-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"' >> ~/.bashrcecho 'export LANGSMITH_PROJECT="your_project"' >> ~/.bashrc
# Reload shell configsource ~/.bashrc

Best Practices

1. Regular Health Checks

# Quick check after making changeslangsmith-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:

1. Export the problematic trace
2. Save to error-cases/ folder
3. Note what went wrong in a README
4. Share trace ID with team

4. Integration with Development

# Before committing codelangsmith-fetch traces --last-n-minutes 10 --limit 5
# If errors foundlangsmith-fetch trace <error-id> --format json > pre-commit-error.json

Quick Reference

# Most common commands
# Quick debuglangsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty
# Specific tracelangsmith-fetch trace <trace-id> --format pretty
# Export sessionlangsmith-fetch traces ./debug-session --last-n-minutes 30 --limit 50
# Find errorslangsmith-fetch traces --last-n-minutes 30 --limit 50 --format raw | grep -i error
# With metadatalangsmith-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