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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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Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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npx skills add https://github.com/Sheshiyer/skill-clusters --skill langsmith-fetchコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
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Zipをダウンロード ダウンロード中... このリポジトリの他の Skills Arcplume runs Grok through the Grok Build CLI's own OAuth-authenticated session (grok login) for image generation, with strict preflight validation, secret-safe handling, and headless CLI-driven execution -- no separate XAI_API_KEY billing. Video falls back to the billed xAI API. USE WHEN a user wants to generate an image via a locally logged-in Grok Build CLI session, e.g. 'generate an image with grok', 'use grok build', or 'use my logged-in grok session'.
Shared reference for the Selemene cluster: the two report surfaces (deterministic Rust reports vs. narrative witness-pipeline readings), the @selemene/bridge CLI contract, the output manifest format, and non-prescriptive witnessing tone. USE WHEN deciding which Selemene surface to invoke or when routing between birth/compatibility/transit reports and solo/dyadic readings.
Route Selemene Engine tasks to the right surface: deterministic reports (birth/compatibility/transit) via selemene-core and the @selemene/bridge CLI, or narrative witness readings via selemene-report. USE WHEN the user wants anything under the Selemene/Noesis umbrella but has not named the exact surface.
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 examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed. cluster agentic-ops version 1.0.0
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"
langsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty
✅ Number of traces found
⚠️ Any errors or failures
🛠️ Tools that were called
⏱️ Execution times
💰 Token usage
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"
langsmith-fetch trace <trace-id> --format json
🎯 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
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 ($0.0276)
Execution Time: 8.7 seconds
Workflow 3: Export Debug Session When user says: "Save this session" or "Export traces"
SESSION_DIR="langsmith-debug/session-$(date +%Y%m%d-%H%M%S) "
mkdir -p "$SESSION_DIR "
langsmith-fetch traces "$SESSION_DIR /traces" --last-n-minutes 30 --limit 50 --include-metadata
langsmith-fetch threads "$SESSION_DIR /threads" --limit 20
✅ 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?"
langsmith-fetch traces --last-n-minutes 30 --limit 50 --format json > recent-traces.json
grep -i "error\|failed\|exception" recent-traces.json
📊 Total errors found
❌ Error types and frequency
🕐 When errors occurred
🎯 Which agents/tools failed
💡 Common patterns
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"
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?"
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"
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"
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
langsmith-fetch traces --after "2025-12-24T13:00:00Z" --limit 20
langsmith-fetch traces --last-n-minutes 60 --limit 100
Include Metadata
langsmith-fetch traces --limit 10 --include-metadata
Concurrent Fetching (Faster)
langsmith-fetch traces ./output --limit 100 --concurrent 10
Troubleshooting
"No traces found matching criteria"
No agent activity in the timeframe
Tracing is disabled
Wrong project name
API key issues
langsmith-fetch traces --last-n-minutes 1440 --limit 50
echo $LANGSMITH_API_KEY
echo $LANGSMITH_PROJECT
langsmith-fetch threads --limit 10
"Project not found"
langsmith-fetch config show
export LANGSMITH_PROJECT="correct-project-name"
langsmith-fetch config set project "your-project-name"
Environment variables not persisting
echo 'export LANGSMITH_API_KEY="your_key"' >> ~/.bashrc
echo 'export LANGSMITH_PROJECT="your_project"' >> ~/.bashrc
source ~/.bashrc
Best Practices
1. Regular Health Checks
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
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
langsmith-fetch traces --last-n-minutes 10 --limit 5
langsmith-fetch trace <error-id> --format json > pre-commit-error.json
Quick Reference
langsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty
langsmith-fetch trace <trace-id> --format pretty
langsmith-fetch traces ./debug-session --last-n-minutes 30 --limit 50
langsmith-fetch traces --last-n-minutes 30 --limit 50 --format raw | grep -i error
langsmith-fetch traces --limit 10 --include-metadata
Resources
Notes for Codex
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
