clinical-question-clarifier

Clarifies a vague clinical or biomedical research idea into a structured, bounded, searchable, researchable, and testable question. Always use this skill whenever a user has an early-stage clinical or research thought, an over-broad topic, an ill-defined evidence question, or an unclear problem statement that must be translated into a question framing suitable for literature retrieval, evidence synthesis, gap analysis, study design, or downstream protocol planning. Never jump straight to answering the substantive medical question unless the user explicitly asks for that. Focus first on question framing, boundary setting, and downstream-ready formulation.

Quality

77%

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Passed

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tessl review fix ./awesome-med-research-skills/Evidence Insight/clinical-question-clarifier/SKILL.md

Quality

Content

67%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.

The body is a well-structured, actionable instruction skill with a clear workflow, ordered output spec, and a clean one-level reference layer. Its main weakness is redundancy across sections that restate the same focusing, routing, and rule guidance.

Suggestions

Merge the trailing 'Interactive Refinement Rule' into the 'Guided Focusing Mode' section, and fold 'Downstream Routing Standard' into Section J / the Core Function, to remove the most obvious duplication.

Consolidate 'Core Function', 'Decision Logic', and 'Hard Rules' so each rule appears once: keep the step sequence as the spine and reference it from the rules list rather than restating both.

Move the inline question-type list and framing-model selection mappings fully into their reference modules (or vice versa) so each piece of guidance lives in exactly one place.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient operational guidance rather than generic concept explanation, but it repeats the same guidance in several places — Guided Focusing Mode vs the Interactive Refinement Rule, Core Function vs Decision Logic vs Hard Rules, and Downstream Routing Standard vs Section J — which could be consolidated.	3 / 5
Actionability	For an instruction-only skill it gives concrete, specific guidance: an 8-step Decision Logic, a mandatory A–K output structure with per-section content, a Section F table template, and explicit framing-model selection mappings.	4 / 5
Workflow Clarity	Steps are clearly sequenced (Decision Logic 1–8 feeding the ordered A–K output) with checkpoint-like gates (researchability assessment in Step 8, Risk-of-Misframing in Section K, stop-when-bounded in focusing mode); this is a non-destructive skill so the validation cap does not apply, but explicit validate→fix→retry loops are absent.	4 / 5
Progressive Disclosure	All ten referenced files in references/ are real and routed one level deep with clear per-section signals, but the body inlines summaries (question-type list, framing-model logic) that duplicate content also placed in the reference files, a minor organization gap.	4 / 5
	Total	15 / 20 Passed

Description

87%Weight 40%Scale 1-5

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

This is a strong, complete description that clearly states what the skill does and when to use it, with natural trigger phrasing and a sharply bounded niche. The only weak spot is mild verbosity around a single composite action padded with adjectives rather than multiple distinct concrete actions.

Dimension	Reasoning	Score
Specificity	The description names its core action ("Clarifies a vague clinical or biomedical research idea into a structured, bounded, searchable, researchable, and testable question") with several concrete facets and downstream use-cases (literature retrieval, evidence synthesis, gap analysis, study design, protocol planning), but it is effectively one composite verb rather than multiple distinct actions, so it does not reach a 5.	4 / 5
Completeness	It explicitly answers both what (clarify/structure a research idea into a testable question) and when ("Always use this skill whenever a user has..." with concrete trigger phrases), matching the top anchor.	5 / 5
Trigger Term Quality	It supplies natural trigger phrases a user would actually say — "early-stage clinical or research thought", "over-broad topic", "ill-defined evidence question", "unclear problem statement" — giving good coverage, though a few common synonyms are missing and no file-extension-style tokens apply to this niche.	4 / 5
Distinctiveness Conflict Risk	It carves a clear niche (clinical/biomedical question framing) with distinct triggers and an explicit boundary ("Never jump straight to answering the substantive medical question"), minimizing conflict with adjacent skills.	5 / 5
	Total	18 / 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/clinical-question-clarifier/SKILL.md
Commit: 63c61d3

Reviewed: 3 hours ago

Table of Contents

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