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.
npx skills add composio-community/awesome-codex-skills --skill langsmith-fetch --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 **E
- When to Use This Skill
- Prerequisites
- 1. Install langsmith-fetch
- 2. Set Environment Variables
- Core Workflows
- Workflow 1: Quick Debug Recent Activity
- 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"
pip install langsmith-fetch export LANGSMITH_API_KEY="your_langsmith_api_key" export LANGSMITH_PROJECT="your_project_name" echo $LANGSMITH_API_KEY echo $LANGSMITH_PROJECT langsmith-fetch traces --last-n-minutes 5 --limit 5 --format pretty langsmith-fetch trace <trace-id> --format json Create session folder with timestamp mkdir -p "$SESSION_DIR" Export traces
What does the langsmith-fetch skill do?
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.
How do I install it?
Run `npx skills add composio-community/awesome-codex-skills --skill langsmith-fetch --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From composio-community/awesome-codex-skills, a repository with 15,591 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.