# Deepeval Tracing

Instrument an AI application with DeepEval's native tracing so its behavior is visible...

- Repository: https://github.com/confident-ai/deepeval (19230 stars)
- Category: Testing
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add confident-ai/deepeval --skill deepeval-tracing -g -a claude-code -y`
Codex: `npx skills add confident-ai/deepeval --skill deepeval-tracing -g -a codex -y`
Cursor: `npx skills add confident-ai/deepeval --skill deepeval-tracing -g -a cursor -y`
Gemini CLI: `npx skills add confident-ai/deepeval --skill deepeval-tracing -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add confident-ai/deepeval`

## Description

Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation, producing well-formed traces, not running evals.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# DeepEval Tracing

Use this skill to instrument an **AI application**, an LLM app, agent, RAG
pipeline, or chatbot, with **DeepEval's native tracing** so its execution is
visible span by span in **Confident AI's Observatory**. The work is: pick a
supported integration when one exists, fall back to manual `@observe`
otherwise, give each span a meaningful type, and add tags and metadata.

This skill stops at producing well-formed traces. Attaching evaluation metrics
and running evals is the `deepeval` skill's job.

## Scope: AI Applications Only

Instrument only the AI parts of the system, agent loops and planning, LLM
calls, retrieval / vector search, and tool calls. The span types (`llm`,
`retriever`, `tool`, `agent`) describe AI components. Do not trace non-AI
software (web servers, CRUD backends, infrastructure). If the target has no
LLM, agent, retrieval, or tool-calling component, this skill does not apply.

## When to Use vs the `deepeval` and `deepeval-otel` Skills

- **This skill (`deepeval-tracing`)**, instrument an app with the DeepEval SDK
  (`@observe`, framework integrations) so traces reach Confident AI.
- **`deepeval` skill**, build pytest eval suites: datasets, metrics, traced
  evals, `deepeval test run`, iteration. It runs evals *against* an app this
  skill instrumented.
- **`deepeval-otel` skill**, instrument with the vendor-neutral OpenTelemetry
  SDK instead of the DeepEval SDK (raw OTLP, including non-Python apps).

The three are complementary. If unsure between this skill and `deepeval-otel`:
use this one when the app is Python and you want the DeepEval SDK; use
`deepeval-otel` when you want raw OpenTelemetry or the app is not Python.

## Prerequisites

- An AI application in Python with `pip install deepeval`.
- For traces to reach Confident AI: `deepeval login`, or an exported
  `CONFIDENT_API_KEY` (preferred for CI and non-interactive runs).

## Workflow

The rest: https://github.com/confident-ai/deepeval/blob/HEAD/docs/public/.well-known/agent-skills/deepeval-tracing/SKILL.md