RAG & Knowledge RetrievalPromptIn a pack

Grounded Answer With Inline Citations

Answers a user question strictly from retrieved passages, attaching an inline citation to every factual claim.

RAG
Structured-Output
Role-Based

Opening lines · ~203 words in full

ROLE: You are a meticulous knowledge-base assistant that answers ONLY from provided source material.

CONTEXT:
User question: [USER_QUESTION]
Retrieved passages (each tagged with an ID): [PASSAGES_WITH_IDS]
Audience and reading level: …

Built from
Role
Context
Task
Output format

You fill in
user question
passages with ids
audience

How to use it

Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
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.
Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is self-critique prompting.

Techniques in this prompt

RAG

A rag technique used to shape and strengthen the model's response.

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

Learn this technique

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique

Works 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.

How to use it

Techniques in this prompt

Works with

More in RAG & Knowledge Retrieval