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name: lay-summary-for-cross-disciplinary-teams description: >- Rewrites technical research content into a structured lay summary that cross-disciplinary teams can quickly understand and act on. Use when the user wants to explain research to colleagues outside their specialty — clinicians, wet-lab scientists, bioinformaticians, product managers, or leadership. Trigger on: "lay summary", "explain my research to the team", "non-technical summary", "cross-disciplinary summary", "translate my findings", "align our team on the study", or any request to communicate research goals, findings, or next steps to a mixed or non-specialist audience. Part of the AIPOCH Academic Writing skill hub. Sits midstream: after research content is clarified, before downstream deliverables like slide decks or graphical abstracts. license: MIT author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Lay Summary for Cross-Disciplinary Teams

Converts technical research into a structured summary that clinical, wet-lab, bioinformatics, product, and management teams can rapidly read and act on.

Position in the Research Pipeline

This skill sits midstream:

• Upstream (should exist first): Clear research question, defined objectives, structured results, result narrative
• This skill: Translates that clarified content for non-specialist readers
• Downstream (natural next steps): Slide Deck for Lab Meeting, Graphical Abstract Generator, Reviewer Response Drafter

If the user's research content is still vague or unstructured, prompt them to clarify objectives and key findings first. A lay summary built on unclear input will sound smooth but be factually imprecise — worse than no summary.

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Step 1 — Gather Input

Ask the user to provide any of:

• Abstract, introduction, or results section
• Key findings in their own words
• A study summary or internal report

Also ask: Who is the primary audience?

• mixed (default) — all teams listed
• clinical — clinicians, medical staff
• wet-lab — bench scientists, experimentalists
• bioinformatics — computational scientists, data analysts
• product — product managers, translational teams
• management — leadership, funders, executives

If unspecified, use mixed and include all relevant audience bullets.

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Step 2 — Extract Core Structure

Before writing, internally map the input to these five elements:

Element	What to find
Study goal	Why was this done? What problem does it address?
System / population	What was studied? (patients, cells, datasets, samples…)
Main finding	What did the data show? Be specific — avoid vague positives.
Evidence boundary	What can this support? What remains uncertain or untested?
Next action	What should each team know or do because of this?

If any element is missing from the input, note it in the output and invite the user to fill in the gap.

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Step 3 — Write the Lay Summary

Use the output template in assets/output-template.md.

Writing principles:

• No unexplained acronyms — define on first use or remove
• Evidence boundary must be explicit: distinguish finding from interpretation
• Each audience bullet should be actionable, not just descriptive
• Quantify findings where possible ("3-fold higher", "in 4 of 6 subtypes")
• The summary must stand alone without access to the original paper

For audience-specific language guidance, read references/audience-guide.md.

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Step 4 — Quality Check

Before delivering output, verify:

• No naked jargon or undefined acronyms
• Finding is accurate — not overstated, not undersold
• Evidence boundary is clearly hedged
• Each audience bullet is actionable
• Summary reads cleanly to someone with no domain knowledge

If a check fails, revise before presenting.

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References

• assets/output-template.md — the standard 6-section output template with example
• references/audience-guide.md — language and framing guidance per audience type