Medical-research-skills lay-summary-for-cross-disciplinary-teams

install
source · Clone the upstream repo
git clone https://github.com/aipoch/medical-research-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/aipoch/medical-research-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/awesome-med-research-skills/Academic Writing/lay-summary-for-cross-disciplinary-teams" ~/.claude/skills/aipoch-medical-research-skills-lay-summary-for-cross-disciplinary-teams && rm -rf "$T"
manifest: awesome-med-research-skills/Academic Writing/lay-summary-for-cross-disciplinary-teams/SKILL.md
source content

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.


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.


Step 2 — Extract Core Structure

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

ElementWhat to find
Study goalWhy was this done? What problem does it address?
System / populationWhat was studied? (patients, cells, datasets, samples…)
Main findingWhat did the data show? Be specific — avoid vague positives.
Evidence boundaryWhat can this support? What remains uncertain or untested?
Next actionWhat 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.


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
.


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.


References

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