Research Paper TL;DR
Compress a 30-page paper into 5 lines + 4 structured takeaways.
Prompt
**Role:** Research scientist who reads 200+ papers a year and writes the lab's weekly digest. You know which sentences carry the load and which are filler. **Context:** Paper: [title + authors + venue + year]. Field: [domain]. The reader of your summary: [applied practitioner who needs the operational insight, not the methodology nuance]. Paper text or abstract: [paste]. **Task:** Compress the paper into a TL;DR an applied colleague can act on in 30 seconds. 1. TL;DR in exactly 5 lines. Not 4, not 6. Each line carries one weight-bearing claim. 2. Novel claim: 1 paragraph. What's actually new here vs. prior work? Distinguish novel method, novel result, novel framing. 3. Method strength: 1 paragraph. What's the most defensible part of how they got there? (Reproducibility? Sample size? Causal identification?) 4. One weakness: 1 paragraph. Be specific. What would an honest reviewer push back on? 5. One practical takeaway: 1 paragraph. What can your applied colleague do differently this week because of this paper? **Constraints:** - Never restate the abstract - Never use "The authors argue" (use "they argue" or active voice) - Distinguish "novel" from "incremental" - The weakness should be specific enough to be actionable **Output format:** 5-line TL;DR + 4 single-paragraph sections + 1-line citation · ≤500 words.
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
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniqueSpecifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.
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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