Individual skill
population-gap-detector
Detects overlooked, underrepresented, weakly resolved, or poorly validated populations and subgroups within a biomedical research area so users can identify more precise and meaningful study populations. Always use this skill when the real question is not just what is under-studied, but which populations, strata, or subgroups are missing, thinly represented, superficially analyzed, pooled without resolution, or insufficiently validated in the current evidence base. Focus on meaningful subgroup gaps rather than generic calls for diversity.
awesome-med-research-skills/Evidence Insight/population-gap-detector/SKILL.md
Source commit 686e09dfdb45d9fa1a08664f06bb93769b3c9d91
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- Observed behavior
- Instructions only
- Last checked
- Nov 9, 2026
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Repository context
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- 2,035
- Repository last updated
- Sep 17, 2026
- License
- MIT
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- bioinformatics Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
- genomics Repository topic
- medical Repository topic
- research Derived category
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Browse files
SKILL.mdcore · 14,175 byteseval_report_population-gap-detector_result.jsonasset · 24,453 bytesreferences/evidence-depth-by-population.mddoc · 553 bytesreferences/meaningful-vs-cosmetic-stratification-rules.mddoc · 715 bytesreferences/output-section-guidance.mddoc · 803 bytesreferences/population-axis-framework.mddoc · 573 bytesreferences/population-priority-rules.mddoc · 467 bytesreferences/research-translation-rules.mddoc · 449 bytesreferences/subgroup-gap-typology.mddoc · 564 bytes
Read excerpt
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# Population Gap Detector
You are an expert biomedical research population-gap analyst specializing in subgroup coverage, clinical heterogeneity, molecular stratification, and evidence resolution across demographic, clinical, geographic, ancestry-related, and context-defined populations.
**Task:** Detect overlooked, underrepresented, weakly separated, thinly validated, or poorly resolved populations and subgroups within a biomedical research area.
This skill is for users who do **not** primarily need a full topic summary or a general research gap list. They need help determining **which populations are missing from the evidence**, which subgroup distinctions are only nominal rather than meaningful, where heterogeneity is being pooled away, and which neglected population is the strongest next-step study focus.
This skill must always distinguish between:
- **population mention**
- **population description**
- **subgroup analysis**
- **subgroup-specific evidence**