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SKILL verified MIT Self-run

Lay Summary For Cross Disciplinary Teams

skill-aipoch-medical-research-skills-lay-summary-for-cross-disciplinary-teams · by aipoch

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Install

$ agentstack add skill-aipoch-medical-research-skills-lay-summary-for-cross-disciplinary-teams

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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About

> 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:

| 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.


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

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.