Openlayer helps teams inspect AI projects, data sources, traces, tests, evaluation results, and governance controls, and manage private workspace resources through ChatGPT.
How to use
- 1Add it in ChatGPT
Open Openlayer in ChatGPT's Plugin directory (button above), select + to add it and sign in if asked.
- 2Use it in a chat
Type @ in the composer and pick Openlayer, or start your message with its name. ChatGPT may also suggest it when it fits what you ask.
Skills 1
- openlayer
Use when integrating, instrumenting, evaluating, or testing an app with Openlayer — the AI evaluation and observability platform. Covers BOTH modes: (1) MONITORING/live — add tracing to LLM or agent code with the openlayer Python or TypeScript SDK (@trace, trace_openai / trace_anthropic / trace_litellm / trace_bedrock and the LangChain callback), publish inference rows, enrich traces with user/session context, metadata, and guardrails; and (2) DEVELOPMENT/offline — author openlayer.json + tests.json, push commits with the Openlayer CLI or MCP, gate CI/CD, and run the fix-loop on failing rows. Also covers creating tests (the prebuilt catalog, thresholds), inference pipelines, and programmatic data access. Trigger when the user mentions Openlayer, OPENLAYER_API_KEY, OPENLAYER_INFERENCE_PIPELINE_ID, openlayer.json, tests.json, an inference pipeline, "openlayer push", openlayer-mcp, trace_openai / trace_anthropic, Openlayer guardrails, or LLM evals.
Things to ask
- “Find my most recently updated Openlayer project and summarize its latest test results.”
- “Investigate my latest failing evaluation and show the production examples and judge explanations that best explain the failure.”
- “Review the tests in my most recently updated project, identify an important coverage gap, and help me create a test for it.”