tracing

Original：🇺🇸 English

Translated

Add LangWatch tracing and observability to your code. Use for both onboarding (instrument an entire codebase) and targeted operations (add tracing to a specific function or module). Supports Python and TypeScript with all major frameworks.

2installs

Sourcelangwatch/skills

Added on2026-04-02

NPX Install

npx skill4agent add langwatch/skills tracing

SKILL.md Content

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Add LangWatch Tracing to Your Code

Determine Scope

If the user's request is general ("instrument my code", "add tracing", "set up observability"):

Read the full codebase to understand the agent's architecture
Study git history to understand what changed and why — focus on agent behavior changes, prompt tweaks, bug fixes. Read commit messages for context.
Add comprehensive tracing across all LLM call sites

If the user's request is specific ("add tracing to the payment function", "trace this endpoint"):

Focus on the specific function or module
Add tracing only where requested
Verify the instrumentation works in context

Detect Context

This skill is code-only — there is no platform path for tracing. If the user has no codebase, explain that tracing requires code instrumentation and point them to the LangWatch docs.

Step 1: Set up the LangWatch MCP

First, install the LangWatch MCP server so you have access to framework-specific documentation:

See MCP Setup for installation instructions.

If MCP installation fails, see docs fallback to fetch docs directly via URLs.

Step 2: Get the API Key

See API Key Setup.

Add the API key to the project's

.env

file:

LANGWATCH_API_KEY=your-key-here

Step 3: Read the Integration Docs

Use the LangWatch MCP to fetch the correct integration guide for this project:

Call
```
fetch_langwatch_docs
```
with no arguments to see the docs index
Find the integration guide matching the project's framework (OpenAI, LangGraph, Vercel AI, Agno, Mastra, etc.)
Read the specific integration page for step-by-step instructions

CRITICAL: Do NOT guess how to instrument. Read the actual documentation for the specific framework. Different frameworks have different instrumentation patterns.

Step 4: Install the LangWatch SDK

For Python:

bash

pip install langwatch
# or: uv add langwatch

For TypeScript:

bash

npm install langwatch
# or: pnpm add langwatch

Step 5: Add Instrumentation

Follow the integration guide you read in Step 3. The general pattern is:

Python:

python

import langwatch
langwatch.setup()

@langwatch.trace()
def my_function():
    # your existing code
    pass

TypeScript:

typescript

import { LangWatch } from "langwatch";
const langwatch = new LangWatch();

IMPORTANT: The exact pattern depends on the framework. Always follow the docs, not these examples.

Step 6: Verify

Run the application and check that traces appear in your LangWatch dashboard at https://app.langwatch.ai

Common Mistakes

Do NOT invent instrumentation patterns — always read the docs for the specific framework
Do NOT skip the
```
langwatch.setup()
```
call in Python
Do NOT forget to add LANGWATCH_API_KEY to .env
Do NOT use
```
platform_
```
MCP tools — this skill is about adding code, not creating platform resources