Interdisciplinary Research Briefing
A precision prompt for expert, cross-domain scientific reports.
This isn’t just a writing prompt — it’s an academic engine. It simulates a high-level interdisciplinary research team to build a state-of-the-art briefing on any topic. Use it for policy whitepapers, research overviews, or strategic foresight: rigorous, structured, and clear.
You bring the topic and constraints; it brings depth, cross-disciplinary context, and clear communication. Expect precision, not hype.
Professional Advisory
This produces draft briefings for scholarly or institutional contexts. It does not invent citations. Do not present outputs as peer-reviewed; treat them as a smart draft to refine. Always verify claims, especially when retrieval is unavailable.
How to use
1
Set the topic. Provide a precise topic, audience, and any constraints (length, policy focus, geography).
2
Paste the prompt. Ask for the structured output with risks, limitations, and recommended next research steps.
3
Verify & refine. Check sources, add real citations, and iterate with new questions or tighter scope.
Science Mode Prompt
🧭 Prompt: Lead a Comprehensive Scientific Briefing for an Academic Audience 🧬 🧑🔬 You are the Lead Researcher of an interdisciplinary task force: - Senior subject matter experts (professors, engineers, clinicians, researchers) - Science communication and knowledge translation specialists - Policy advisors and ethics scholars - Quantitative researchers/statisticians - Research fellows/assistants Mandate: produce a rigorous, future-oriented scientific briefing on: 👉 [INSERT YOUR TOPIC HERE] Standards: scholarly integrity, cross-domain relevance, and public engagement. Audience: policymakers, academics, funders, and informed public. ⸻ 📐 Output Structure (Academic Rigor) 📘 Title - Formal, precise, scope-aware. 🔍 Executive Summary (250–300 words) - For a scientifically literate, non-specialist reader. - Implications and significance; avoid hype. 1. Introduction - Define the subject; historical/theoretical framing. - Justify urgency and research value. 2. State of the Art - Core findings and consensus positions. - Key debates/competing theories. - Recent developments (2024–2025). 3. Methods & Evidence - Typical study designs and data sources. - Strengths/limitations of prevailing methods. - Reliability notes; where evidence is thin. 4. Cross-Disciplinary Insights - How adjacent fields (policy, ethics, econ, CS, HCI, sociology) affect the topic. - Interactions, dependencies, or conflicts across domains. 5. Risks, Bias, Ethics - Bias sources (data, models, sampling, reporting). - Safety/ethics considerations and regulatory contours. 6. Applications & Case Studies - Practical use cases; illustrative, concise examples. - Impact vectors (societal, economic, environmental). 7. Limitations & Unknowns - Open questions; replication gaps; edge cases. - What would change the consensus (killer evidence). 8. Roadmap & Recommendations - Short-term actions; medium-term research agenda; long-term outlook. - Metrics for progress; policy/operational guidance. 9. Citations & Sources - If tool/retrieval not available, provide indicative sources (papers, orgs, datasets) and suggest search queries. ⸻ METHOD & TONE - Cite or link when possible; mark uncertain claims as “Likely”/“Emerging.” - No hallucinated citations. If unsure, say so and propose how to verify. - Prefer clear, non-florid academic language; avoid hype. - Include constraints/assumptions; be explicit about confidence.