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tracing

Instrument Python and TypeScript applications with OpenTelemetry-based tracing via Traceloop SDK.

13|Updated Feb 13, 2026
Search Tags:#typescript#debugging#python#llm#observability#tracing#opentelemetry
One-click install
npx skills add https://github.com/truefoundry/tfy-agent-skills --skill tracing-truefoundry
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tracing
Source: https://github.com/truefoundry/tfy-agent-skills/tree/main/skills/tracing
Command: npx skills add https://github.com/truefoundry/tfy-agent-skills --skill tracing-truefoundry

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires traceloop-sdk, @traceloop/node-server-sdk, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the process of adding distributed tracing to your applications, providing deep visibility into request flows, LLM interactions, and custom application logic.

Core Features & Use Cases

  • Automated Instrumentation: Integrates OpenTelemetry and the Traceloop SDK for Python and TypeScript.
  • LLM Observability: Automatically captures LLM calls made by popular libraries.
  • Custom Spans: Allows manual instrumentation of application-specific workflows and tasks.
  • Use Case: You've built a complex RAG pipeline involving multiple LLM calls and data retrieval steps. Use this Skill to instrument the application, visualize the entire pipeline execution, identify bottlenecks, and debug LLM interactions.

Quick Start

Use the tracing skill to instrument my Python application with Traceloop.

Frequently Asked Questions about tracing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add OpenTelemetry tracing to a Python or TypeScript application?▼

To add OpenTelemetry tracing, you instrument your application code using the Traceloop SDK, which automatically captures request flows and custom application logic for visualization.

Can I capture LLM calls automatically when instrumenting my application for observability?▼

Yes, LLM observability is supported natively. The tracing instrumentation automatically captures LLM calls made by popular libraries, allowing you to debug interactions and identify bottlenecks.

What is the best way to trace a complex RAG pipeline involving multiple LLM calls?▼

Tracing a complex RAG pipeline is best handled by creating custom spans to instrument data retrieval steps and LLM calls, providing deep visibility into the entire pipeline execution flow.

Do I need TrueFoundry credentials to set up distributed tracing with this approach?▼

Yes, valid TrueFoundry credentials are required. You need Bash and curl to facilitate creating tracing projects and integrating the TrueFoundry Tracing Platform with your application.

Does this tracing instrumentation work with both Python and TypeScript environments?▼

Yes, the instrumentation works with both Python and TypeScript. It integrates OpenTelemetry and the Traceloop SDK to capture distributed traces across both programming environments.

How do custom spans help with debugging application workflows?▼

Custom spans allow manual instrumentation of application-specific workflows. By creating custom spans, you can trace distinct tasks within your logic to pinpoint execution bottlenecks and debug issues.

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