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ComposioHQ/awesome-claude-skills62.1k

langsmith-fetch

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 examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

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$npx clawhub@latest install langsmith-fetch

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Overview

# 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"

Validate with a real task

Run one small real task before keeping it in your long-term workflow.

**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 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)

```bash

langsmith-fetch traces --limit 5 --format pretty

```

**Use for:** Quick visual inspection, showing to users

JSON Format

```bash

langsmith-fetch traces --limit 5 --format json

```

**Use for:** Detailed analysis, syntax-highlighted review

Raw Format

```bash

langsmith-fetch traces --limit 5 --format raw

```

**Use for:** Piping to other commands, automation

---

Advanced Features

Time-Based Filtering

```bash

# 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

```bash

# Get extra context

langsmith-fetch traces --limit 10 --include-metadata

# Metadata includes: agent type, model, tags, environment

```

Concurrent Fetching (Faster)

```bash

# Speed up large exports

langsmith-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:**

```bash

# 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:**

```bash

# 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:**

```bash

# 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

```bash

# 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:

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

```bash

# 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

```bash

# 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

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Skill Info

Namelangsmith-fetch

RepoComposioHQ/awesome-claude-skills

Stars62.1k

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langsmith-fetch

Copy first, validate next

Copy the install command

Check source and behavior

Overview

When to Use This Skill

Prerequisites

1. Install langsmith-fetch

2. Set Environment Variables

Core Workflows

Workflow 1: Quick Debug Recent Activity

Validate with a real task

Workflow 2: Deep Dive Specific Trace

Workflow 3: Export Debug Session

Workflow 4: Error Detection

Common Use Cases

Use Case 1: "Agent Not Responding"

Use Case 2: "Wrong Tool Called"

Use Case 3: "Memory Not Working"

Use Case 4: "Performance Issues"

Output Format Guide

Pretty Format (Default)

JSON Format

Raw Format

Advanced Features

Time-Based Filtering

Include Metadata

Concurrent Fetching (Faster)

Troubleshooting

"No traces found matching criteria"

"Project not found"

Environment variables not persisting

Best Practices

1. Regular Health Checks

2. Organized Storage

3. Document Findings

4. Integration with Development

Quick Reference

Resources

Notes for Claude

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