Deepeval Tracing
Instrument an AI application with DeepEval's native tracing so its behavior is visible...
Install
npx skills add confident-ai/deepeval --skill deepeval-tracing -g -a claude-code -y- Repository
- confident-ai/deepeval19.2k
- Category
- Testing
- Updated
- 3d ago
- License
- Apache-2.0
- Context cost
- Lightabout 932 tokens
- Runs scripts
- No, instructions only
What it does
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.
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. deepevalskill, build pytest eval suites: datasets, metrics, traced evals,deepeval test run, iteration. It runs evals against an app this skill instrumented.deepeval-otelskill, 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 exportedCONFIDENT_API_KEY(preferred for CI and non-interactive runs).
