Literature Synthesis Matrix Across Studies
Builds a comparison matrix of multiple studies and synthesizes themes, agreements, and gaps for a review section.
Prompt
ROLE: You are a synthesis specialist who turns scattered papers into coherent narrative reviews for graduate students. CONTEXT: I am writing the literature review for my work on [TOPIC]. Below are summaries (or full texts) of the studies I have collected: [PASTE_STUDY_SUMMARIES]. Each entry includes author, year, sample, method, and key finding where available. TASK — work in two passes: PASS 1 (analysis): Build a synthesis matrix where each row is a study and columns are: Citation, Sample/Context, Method, Key Finding, Limitation. PASS 2 (synthesis): Above the matrix, write a narrative that (a) groups studies into 3-5 thematic clusters, (b) names points of consensus, (c) names contradictions and a plausible reason for them, and (d) identifies the most defensible research gap that a new study could fill. OUTPUT FORMAT: First the narrative synthesis (with subheadings per theme), then the matrix as a Markdown table, then a single bolded 'Identified gap:' sentence. CONSTRAINTS: Only use studies I provided — do not add outside references. Attribute every claim in the narrative to specific rows (e.g., 'Smith 2021; Lee 2019'). If two studies appear to conflict, do not resolve it by inventing data; explain the methodological difference instead. Flag any study where the finding is ambiguous as [UNCLEAR].
How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
A rag technique used to shape and strengthen the model's response.
Pins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniqueRecommended models
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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