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keyword-research

When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.

70

Quality

85%

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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 solid, well-structured instruction-only skill: the research workflow is clearly phased, guidance is quantified and templated, and it stays lean without explaining general concepts. The main gaps are the unspecified data source for volume/difficulty and competitor rankings, implicit rather than explicit validation checkpoints, and mild padding (persona line, 'Why it matters' column).

Suggestions

Specify how to obtain volume, difficulty, and competitor-ranking data (which tool, API, or fallback to manual estimates) — currently Phase 1-2 assume data with no source.

Add an explicit validation checkpoint before delivering the strategy, e.g. 'Verify title/subtitle fit within 30 chars and the keyword field within 100 before presenting'.

Trim the persona preamble and the 'Why it matters' table column — both restate knowledge the phase guidance already conveys.

DimensionReasoningScore

Conciseness

Mostly efficient, domain-specific content (char limits, indexing rules) that Claude would not reliably know, with only minor trimmable padding — the role persona line ('You are an expert ASO keyword researcher...') and the 'Why it matters' table column explain things Claude can infer. Not 5 due to those small instances of over-explanation; not 3 because there are no padded concept explanations.

4 / 5

Actionability

Concrete, actionable instruction-only guidance: an exact opportunity formula, quantified keyword buckets (3-5 primary, 5-10 secondary, 10-20 long-tail), and a fill-in output template with explicit char limits. Not 5 because how to actually obtain volume/difficulty data and competitor rankings is left unspecified; not 3 because the guidance is specific and templated rather than pseudocode-level.

4 / 5

Workflow Clarity

A clearly sequenced four-phase process (Seed Expansion → Evaluation → Opportunity Scoring → Grouping) preceded by an explicit initial assessment with defaults. Not 5 because validation checkpoints are only implicit (e.g., no step verifying the 30/100-char limits before delivering the strategy); not 3 because the sequence is explicit and well-defined, and this is non-destructive research so no hard cap applies.

4 / 5

Progressive Disclosure

Well-organized, self-contained body with clean section headers and only one-level references (the app-marketing-context.md check and the related-skills list); no bundle files exist. Not 5 because at ~135 lines it exceeds the under-50-line simple-skill exception and the body is monolithic rather than splitting any detail into references; not 3 because structure and navigation are good with nothing buried.

4 / 5

Total

16

/

20

Passed

Description

95%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 names a specific domain, lists concrete actions, provides an explicit and natural trigger clause with multiple user phrasings, and proactively disambiguates from sibling skills. The only soft spot is that the action verbs could be more operationally concrete.

DimensionReasoningScore

Specificity

Names the domain ('App Store keywords') and lists several specific actions ('discover, evaluate, or prioritize'), with minor gaps — the actions are less concrete than fully enumerated operations. Not 3 because it goes beyond 1-2 actions and covers the workflow; not 5 because 'discover' and 'evaluate' are not as concrete as the anchor's enumerated operations.

4 / 5

Completeness

Explicitly answers both what ('discover, evaluate, or prioritize App Store keywords') and when ('Also use when the user mentions...') with concrete trigger phrases. Not 4 because the when-clause is fully explicit rather than partially implied.

5 / 5

Trigger Term Quality

Comprehensive natural trigger phrasings users would actually say: 'keyword research', 'find keywords', 'search volume', 'keyword difficulty', 'keyword ideas', 'what keywords should I target' — covering synonyms and full query phrasings, matching the comprehensive anchor.

5 / 5

Distinctiveness Conflict Risk

Clear ASO keyword-research niche with explicit disambiguation from sibling skills ('For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit'), giving minimal conflict risk. Not 4 because the overlap with closely related skills is actively resolved in the description itself.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Eronred/aso-skills
Reviewed

Table of Contents

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