Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or e
Scanned 9/11/2026
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---
name: langsmith-fetch
description: Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or e
category: Development & Code Tools
source: composio
tags: [node, api, git, github, json, cli, automation, ai, claude]
url: https://github.com/ComposioHQ/awesome-claude-skills/tree/master/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
```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_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:**
```bash
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 tool
2. Filter deleted nodes in search results
3. Update cache invalidation strategy
Token Usage: 1,842 tokens ($0.0276)
Execution Time: 8.7 seconds
```
---
### Workflow 3: Export Debug Session
**When user says:** "Save this session" or "Export traces"
**Execute:**
```bash
# Create session folder with timestamp
SESSION_DIR="langsmith-debug/session-$(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:**
```bash
# 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:**
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: 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:**
1. Check if traces exist:
```bash
langsmith-fetch traces --last-n-minutes 5 --limit 5
```
2. **If NO traces found:**
- Tracing migh
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