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.

Quality

80%

Does it follow best practices?

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Securityby

Passed

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Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured analytical skill body with a clear sequenced workflow, strong progressive disclosure, and concrete taxonomies; its main weakness is redundancy of the core distinctions across several sections.

Suggestions

Consolidate the mention-vs-evidence and should/should-not distinctions into one authoritative section (e.g., Hard Rules) and reference it from Core Function and What This Skill Should Not Do to remove repetition.

Add a brief inline extract of the most load-bearing operational rule from each reference module so the skill remains actionable even before the reference is opened.

Promote the Section I Risk Review into an explicit pre-output validation checkpoint (e.g., 'Before finalizing, confirm the gap survives the Risk Review criteria') to strengthen feedback-loop clarity.

Dimension	Reasoning	Score
Conciseness	The body is lean and does not explain concepts Claude already knows, but the mention-vs-evidence distinction and the should/should-not framing are restated across Core Function, Decision Logic, Hard Rules, What This Skill Should Not Do, and Quality Standard, so some repetition could be trimmed.	4 / 5
Actionability	Concrete analytical guidance is provided throughout (explicit axis lists, gap-type taxonomies, evidence-depth tiers, prioritization criteria, and a per-section output template), but the actual operational rules are deferred to the reference modules rather than stated inline, leaving minor gaps.	4 / 5
Workflow Clarity	An explicit 8-step sequence is given with each step mapped to a reference module, plus an out-of-scope stop gate and an incompleteness check; validation is folded into the output (Section I Risk Review) rather than presented as discrete checkpoints, so it is just below anchor 5.	4 / 5
Progressive Disclosure	The body is a clean overview that delegates operational rules to seven real one-level-deep reference files, each clearly signaled with the exact output section it supports, with all referenced paths verified to exist.	5 / 5
	Total	17 / 20 Passed

Description

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Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, highly specific description with explicit trigger guidance and a clear niche; its only weakness is that the action vocabulary is narrow (detect/identify/focus) rather than a rich list of concrete operations.

Dimension	Reasoning	Score
Specificity	The description names the domain richly and gives one concrete detect/identify action ('Detects overlooked, underrepresented, weakly resolved, or poorly validated populations and subgroups'), but the rest of the verbs ('Focus on meaningful subgroup gaps') describe target emphasis rather than distinct actions, so it does not reach the multi-action coverage of anchor 4.	3 / 5
Completeness	It explicitly answers both 'what' (detects overlooked/underresolved populations and subgroups) and 'when' via a concrete 'Always use this skill when...' clause listing specific trigger conditions, matching the anchor 5 example.	5 / 5
Trigger Term Quality	Strong natural trigger coverage ('under-studied', 'which populations...are missing', 'thinly represented', 'pooled without resolution', 'subgroup gaps') that a user would plausibly say, but the terms skew clinical and omit plainer lay synonyms, so it sits just below the comprehensive anchor 5.	4 / 5
Distinctiveness Conflict Risk	The niche is sharply defined (population/subgroup gaps in biomedical evidence, meaningful vs cosmetic stratification) with distinct triggers, giving minimal overlap with a generic research-gap finder.	5 / 5
	Total	17 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Path: awesome-med-research-skills/Evidence Insight/population-gap-detector/SKILL.md
Commit: f5ef65b

Reviewed: ~12 hours ago

Table of Contents

Discovery Implementation Validation

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