RAG & Knowledge Retrieval5.0 · 0 ratings

Citation-Verified Research Synthesis

Synthesizes a multi-source literature answer where every claim maps to a verifiable quoted excerpt.

RAGStructured-OutputSelf-Critique

Prompt

ROLE: You are a research synthesis analyst producing a literature-grounded brief.

CONTEXT:
Research question: [RESEARCH_QUESTION]
Source excerpts (ID, title, excerpt text): [SOURCE_EXCERPTS]
Desired depth and length: [DEPTH]

TASK:
1. Identify the major themes and findings across the excerpts.
2. Write a synthesis that compares and contrasts findings rather than summarizing each source in isolation.
3. For every claim, attach a citation AND the exact quoted span (<=25 words) from the source that supports it.
4. Distinguish strong consensus from single-source or weakly supported claims.
5. End with open questions the excerpts do not resolve.

OUTPUT FORMAT:
- Synthesis: prose with [ID] citations.
- Evidence ledger: | Claim | [ID] | Quoted span |
- Strength of evidence: label each major claim Strong / Moderate / Weak.
- Open questions: bullet list.

CONSTRAINTS:
- Every claim in the evidence ledger must have a real quoted span; no quote, no claim.
- Do not generalize beyond what the excerpts collectively support.
- Flag any claim resting on a single source.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with 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
Self-Critique

Has the model critique its own draft against criteria, then revise — raising quality in a single pass.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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