Individual skill

genai-hub-prompt-evaluation

Run GenAI evaluations on SAP AI Core: benchmark LLMs and prompts against a test dataset using system-defined and custom (LLM-as-judge) metrics, then retrieve aggregate results. Supports all three evaluation types — prompt registry, orchestration registry, and grounding (RAG) orchestration registry. WHEN: user wants to evaluate or benchmark an LLM / prompt / orchestration config, run a GenAI evaluation, create or list evaluation metrics, define a custom LLM-as-a-judge metric, create a prompt template (prompt registry) or an orchestration-registry config (with or without grounding) for evaluation, create an evaluation configuration or execution, or fetch evaluation results / scores for an execution. DO NOT USE FOR: agent evaluation via the offline aeval service — use `aeval-offline-evaluation`; building a production orchestration/RAG pipeline for inference — use `genai-hub-orchestration`; generic executions, deployments, or artifacts unrelated to evaluation — use `aicore-lifecycle-management`; credentials, resource groups, or object stores — use `aicore-admin-resources`.

plugins/aicore-skills/skills/genai-hub-prompt-evaluation/SKILL.md

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Nov 5, 2026
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## Step 0 — ask for credentials first (required)

Before running any other step, confirm the AI Core credentials are set. Invoke
`aicore-admin-resources` and run `check_setup.py`.

- If it succeeds, continue to the workflow.
- If it fails (missing variables, `invalid_client`, or bad credentials), **STOP and ask the user**
  to export the variables listed in **Environment variables** below. Do not continue, and do not
  look for credentials or workflow steps anywhere else (notebooks, other repos, workspace files) —
  this skill's `scripts/` are the only supported path.

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## Rules
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