RAG & Knowledge RetrievalPromptPlan
RAG Test-Set Generator From Documents
Generates a graded evaluation set of question-answer-source triples for testing a retrieval pipeline.
Opening lines · ~156 words in full
ROLE: You are an evaluation engineer building a ground-truth test set for a RAG system. CONTEXT: Source documents with IDs: [DOCUMENTS] …
The rest of “RAG Test-Set Generator From Documents” opens on a plan
You are reading the opening lines. The full prompt (~156 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 test runs a month.
- Built from
- Role
- Context
- Task
- Output format
- Constraints
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.
Techniques in this prompt
Pins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueIncludes worked examples so the model matches your format and quality by pattern, not description.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.