CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

nhanes-clinical-retrospective-biomarker-research-planner

Generates complete NHANES-style cross-sectional epidemiology + retrospective clinical validation research designs from a user-provided disease and biomarker direction. Always use this skill whenever a user wants to design, plan, or build a population-level biomarker association study using NHANES or similar survey datasets, especially when the article logic includes disease definition, biomarker formula derivation, multivariable logistic regression, restricted cubic spline analysis, subgroup stability testing, and a secondary hospital-based retrospective validation cohort. Covers five study patterns (cross-sectional association, dose-response / RCS, subgroup-stability, NHANES + retrospective validation, preliminary screening-performance) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...

Quality

87%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

77%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, highly actionable instruction skill: clear 7-step sequence with mandatory pre-output validation and feedback loops, excellent one-level-deep reference splitting, and concrete output contracts. Its main weakness is redundancy — many rules are stated twice (inline in steps and again in Hard Rules), inflating token cost without adding information.

Suggestions

Remove the near-verbatim duplication between Step 5's dependency rules / Section D's disclaimer / Section I's citation rules and Hard Rules 16-23 — keep the canonical statement in one place and have the Hard Rules reference it, saving significant tokens.

Name the 8 workflow fields inline (at least as a one-line list) in Step 6 so the body is self-contained and the reference file serves as expansion rather than a required lookup for basic compliance.

Trim the description-echoing preamble and Sample Triggers section, which overlap heavily with the frontmatter description and the Input Validation examples.

DimensionReasoningScore

Conciseness

The body does not explain concepts Claude already knows, but it is noticeably repetitive: the dependency/forbidden-module rules of Step 5 are restated nearly verbatim in Hard Rules 16-19, the Dataset Disclaimer appears both in Section D and Hard Rule 22, Step 4.5 citation rules repeat in Section I and Hard Rules 11-13, and Section J's requirements repeat in Hard Rule 23. This matches anchor 3 ('mostly efficient but... could be tightened') rather than 2, since the padding is rule duplication rather than concept explanation or fluffy prose.

3 / 5

Actionability

Concrete, specific guidance throughout: an exact input format with worked examples, an exact out-of-scope redirect script, config comparison tables, explicit dependency formulas (e.g., 'disease definition + biomarker formula + adjusted logistic association + RCS'), a verbatim disclaimer line, and exact output section categories I1-I4 with fallback phrases like 'no directly verified reference identified yet'. It falls short of anchor 5 only because some executable detail is deferred without inline summary (e.g., Step 6 mandates 'include all 8 fields' but never names the 8 fields, and literature retrieval steps depend on unspecified search tooling) — minor gaps, matching anchor 4.

4 / 5

Workflow Clarity

The 7 steps are explicitly ordered ('always run in order') with a mandatory validation checkpoint before output (Step 5 'Dependency Consistency Check (mandatory before output)') and a feedback loop ('If any dependency inconsistency is found, revise the plan before outputting'). Scope rejection is scripted, defaults are stated ('recommend Standard as primary'), and the output contract is enumerated as mandatory sections A-J. This matches anchor 5: clear sequence, explicit validation, error-recovery loop, and checklists.

5 / 5

Progressive Disclosure

The body is an orchestrating overview that delegates detail to eight well-labeled, one-level-deep reference files, each cited with a clear signal of what it contains ('→ Detailed pattern logic: [references/study-patterns.md]', '→ 8-field template + module library: [references/workflow-step-template.md]', etc.), and all eight referenced paths exist in references/. Navigation is easy and nothing is nested two levels deep, matching anchor 5.

5 / 5

Total

17

/

20

Passed

Description

92%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.

A strong description: it explicitly states what the skill produces (research designs, five study patterns, four workload configs) and when to use it, in third person, with a clear niche and low conflict risk. The main weakness is length and jargon density — trimming methodological terms and adding a few more natural user phrasings would improve trigger-term quality.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions and outputs: 'Generates complete NHANES-style cross-sectional epidemiology + retrospective clinical validation research designs', 'always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path'. Coverage of what the skill produces is comprehensive and concrete, matching the score-5 anchor; it is not the level-4 anchor because there are no meaningful gaps in the enumerated capabilities.

5 / 5

Completeness

Both 'what' and 'when' are explicit and concrete: what — 'Generates complete... research designs from a user-provided disease and biomarker direction' with the five study patterns and four configs; when — 'Always use this skill whenever a user wants to design, plan, or build a population-level biomarker association study using NHANES or similar survey datasets, especially when...'. This matches the score-5 anchor with a clear trigger clause; it is not below 5 because the 'when' clause is explicit with concrete triggering conditions rather than weakly implied.

5 / 5

Trigger Term Quality

Good keyword coverage with natural terms users would say: 'design, plan, or build a population-level biomarker association study using NHANES', 'disease', 'biomarker', 'retrospective validation'. It misses some common natural variations (e.g., 'survey data analysis', 'prevalence study', 'cross-sectional study') and leans on technical jargon like 'restricted cubic spline analysis', so it sits between anchor 4 ('good keyword coverage; a few natural terms missing') and anchor 5 — noticeably above the midpoint but not comprehensive.

4 / 5

Distinctiveness Conflict Risk

The description carves out a clear niche — NHANES-style population biomarker association studies with retrospective clinical validation — with trigger terms ('NHANES', 'biomarker', 'hospital-based retrospective validation cohort') that would almost never collide with unrelated skills. It matches anchor 5 ('clear niche with distinct triggers; minimal conflict risk'); anchor 4 would require some overlap with closely related skills, which is not evident here.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

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/Protocol Design/nhanes-clinical-retrospective-biomarker-research-planner/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.