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react-doctor

Use when finishing a feature, fixing a bug, before committing React code, or when the user wants to improve code quality or clean up a codebase. Checks for score regression. Covers lint, dead code, accessibility, bundle size, architecture diagnostics.

73

Quality

91%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is react-doctor in millionco/react-doctor

SKILL.md
Quality
Evals
Security

Quality

Content

100%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 content is lean, fully actionable, and provides explicit validation checkpoints for a diagnostic workflow, while being well organized with no need for external references. It is a model for a simple, single-purpose skill.

DimensionReasoningScore

Conciseness

The body is lean — short labeled sections, a single command, and a compact flag table — with no over-explanation of React or linting concepts, so every token earns its place.

5 / 5

Actionability

It gives the exact executable command `npx -y react-doctor@latest . --verbose --diff` in both scenarios plus a flag table mapping each flag to its purpose, making the guidance copy-paste ready and covering common cases.

5 / 5

Workflow Clarity

Two clearly sequenced workflows each include an explicit validation checkpoint ('check the score did not regress' / 'If the score dropped, fix the regressions before committing' and 'Fix issues by severity — errors first, then warnings'), providing a validate-and-fix feedback loop for this diagnostic operation.

5 / 5

Progressive Disclosure

This is a short (~35 line) single-purpose skill with no bundle files and well-organized section headers plus a flag table, satisfying the simple-skill exception for progressive disclosure.

5 / 5

Total

20

/

20

Passed

Description

83%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 with an explicit 'Use when...' trigger clause, a clear statement of what it does, and React-specific scoping that keeps conflict risk low. It could push toward a perfect score by converting its diagnostic categories into concrete actions and adding a few synonym triggers.

DimensionReasoningScore

Specificity

Quotes concrete capabilities ('Checks for score regression', 'Covers lint, dead code, accessibility, bundle size, architecture diagnostics') naming several specific areas, though these are diagnostic categories rather than actions, leaving minor coverage gaps versus a comprehensive 5.

4 / 5

Completeness

Explicitly answers 'what' (checks for score regression, covers lint/dead code/accessibility/bundle size/architecture) and 'when' ('Use when finishing a feature, fixing a bug, before committing React code, or when the user wants to improve code quality or clean up a codebase') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural triggers like 'finishing a feature', 'fixing a bug', 'before committing React code', 'improve code quality', and 'clean up a codebase' are phrases users would naturally say, with good keyword coverage but a few synonyms missing.

4 / 5

Distinctiveness Conflict Risk

Scoped to React codebases with specific diagnostic categories and React-tied triggers, making it mostly distinct with only minor overlap risk against generic lint/cleanup skills.

4 / 5

Total

17

/

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.

Validation15 / 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
MapleTechLabs/maple
Reviewed

Table of Contents

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