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Agent Skills are packaged instructions that condition AI coding assistants — Claude Code, Cursor, and others — to follow a tool’s current best practices instead of guessing from memory. The Openlayer skill teaches your coding agent how to wire a codebase into Openlayer end to end:
  • Tracing / monitoring — instrument LLM and agent code with the Python or TypeScript SDK and publish traces.
  • Offline evals — set up openlayer.json + tests.json, push commits, and read results.
  • Tests and guardrails — create tests from the catalog and configure guardrails.
  • CI/CD gating — fail builds on eval regressions.
  • Data and docs access — query your workspace and search the Openlayer documentation via the Openlayer MCP server.
It covers both LLM applications and traditional/tabular ML models (scikit-learn, XGBoost, and similar). With the skill installed, agents stop producing outdated SDK calls, wrong environment variables, or invented test configs — they follow the same conventions our own team uses.

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Installation

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Prerequisites

An Openlayer account and an API key:
Find your API key under Workspace settings → API keys (see Find your API key). If you run a self-hosted Openlayer instance, also set OPENLAYER_BASE_URL.

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Usage

Once installed, the agent uses the skill automatically whenever a task touches Openlayer — for example:
  • “Add Openlayer tracing to this agent.”
  • “Set up offline evals for this repo and push a commit.”
  • “Create tests for hallucination and PII, and gate CI on them.”
The skill source lives at github.com/openlayer-ai/openlayer-skills.