deepeval-tracing

deepeval-tracing is an LLM evaluation & observability skill for AI agents, published by confident-ai in the deepeval repository on GitHub. Skillspace rates deepeval-tracing D (66/100) and it passed the safety scan; the rating is based on static analysis only.

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.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

18,247

Unproven: rated by static analysis only, not yet compared head-to-head.

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