skills

Create and manage evaluation datasets in Adaline. Use when building test cases, adding dataset columns/rows, importing data, or triggering dynamic columns.

Fetch deployed prompt snapshots from Adaline at runtime. Use when integrating prompt deployments, environment-based latest lookups, prompt caching, or pinned deployment IDs.

Run and manage evaluations in Adaline to test prompt quality at scale. Use when creating evaluation runs, polling status, analyzing results, or cancelling runs.

Create and manage evaluators in Adaline to score prompt outputs. Use when setting up LLM-as-a-judge, JavaScript, text-matcher, cost, latency, or response-length evaluators.

High-level guide for integrating your AI application with Adaline. Use when starting a new Adaline integration, choosing between API/SDK approaches, or planning which Adaline features to adopt.

Send traces and spans to Adaline for AI agent observability. Use when instrumenting LLM calls, tools, retrieval, embeddings, guardrails, or custom operations.

Create and manage prompts in Adaline via the v2 API or SDK clients. Use when programmatically creating prompts, updating prompt drafts, listing prompts, or reading prompt/playground data.

List configured AI providers and models in Adaline. Use when discovering available LLM providers, filtering models, or checking provider configuration.