Agent skill · confident-ai
deepeval-otel
Export raw OpenTelemetry traces from an AI application to Confident AI's Observatory. TRIGGER when the user wants to send OpenTelemetry or OTLP traces/spans from an LLM app, agent, RAG pipeline, or chatbot to Confident AI; configure the Confident AI OTLP endpoint; set confident.span.* or confident.trace.* attributes; export AI-app traces without the deepeval Python package; wire an OTLPSpanExporter, OpenTelemetry Collector, or vendor-neutral OTel SDK to Confident AI; or pick the US vs EU OTLP endpoint. Language-agnostic: the mechanism is OTLP attribute keys plus an exporter endpoint. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill); for instrumenting with the DeepEval SDK's @observe decorator or framework integrations (use the `deepeval-tracing` skill); or for non-AI software such as web servers, CRUD backends, or infrastructure: the confident.* attributes describe AI components only.
What it needs
About 4k tokens when loaded.
What this skill does
DeepEval OpenTelemetry Export Use this skill to instrument an AI application — an LLM app, agent, RAG pipeline, or chatbot — with raw OpenTelemetry so its traces land in Confident AI's Observatory. No deepeval package is needed — it works with any OTLP-capable OpenTelemetry SDK. The job is exactly two things: export to the correct Confident AI OTLP endpoint, and set the confident. attributes Confident AI reads off each span. Scope: AI Applications Only This skill instruments AI applications only. The confident. attributes and span types — agent, llm, retriever, tool — describe AI components, and Confident AI's Observatory is built to evaluate and monitor AI behavior. Instrument only the AI parts of the system: agent loops and planning, LLM calls, retrieval / vector search, and tool calls. Do not apply confident. attributes to non-AI software (web servers, CRUD backends, database layers, infrastructure) or to non-AI spans inside an otherwise-AI app — that data does not belong in Confident AI and will not render meaningfully. If the target has no LLM, agent, retrieval, or tool-calling component, this skill does not apply. When to Use vs the deepeval Skill Use this skill for vendor-neutral OTLP export to Confident AI — pointing an OpenTelemetry exporter at Confident AI and setting confident. attributes. Use the deepeval skill when the user wants to build a Python pytest eval suite, generate datasets or goldens, write metrics, run deepeval test run, or instrument with the deepeval SDK's @observe decorator. The two skills are complementary, not alternatives. Prerequisites A Confident AI account and a CONFIDENTAPIKEY. An OpenTelemetry SDK for the application's language. For Python: opentelemetry-sdk and opentelemetry-exporter-otlp-proto-http. The Confident AI OTLP endpoint accepts HTTP only — never gRPC. How It Works Confident AI exposes an OTLP/HTTP traces endpoint. Point any OpenTelemetry span exporter at it with the x-confident-api-key header. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills confident-ai/deepeval-otel--6d224b