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app-store-optimization

Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

1.22x
Quality

55%

Does it follow best practices?

Impact

94%

1.22x

Average score across 3 eval scenarios

SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/app-store-optimization/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

25%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-headed but bloated capability catalog that describes rather than instructs: no runnable code or commands, no sequenced workflows with validation, and eight documented scripts that are missing from the bundle entirely. Its main assets are the concrete platform character limits and JSON input/output schemas, which keep it above the lowest scores.

Suggestions

Either ship the eight documented scripts in scripts/ or remove the Scripts section; right now Claude is told to rely on files that do not exist.

Add executable invocation guidance: how to run each script (command line with arguments) and a worked end-to-end workflow (keyword research -> metadata optimization -> character-limit validation -> tracking) with an explicit validation checkpoint before submitting metadata.

Move the Best Practices, Limitations, and Integration sections into one or two reference files (e.g., references/best-practices.md) and cut the seven duplicate 'Hey Claude' sample prompts to one or two, shrinking SKILL.md to a lean overview with clearly signaled one-level-deep references.

DimensionReasoningScore

Conciseness

At ~400 lines the body is noticeably verbose with several padded sections: seven near-identical "Hey Claude..." sample prompts, generic ASO best-practice lists Claude largely already knows (respond to reviews quickly, front-load keywords), and an "Integration with Other Skills" section. Not a 1 because the platform character limits and script API listings are genuine reference content delivered in structured form.

2 / 5

Actionability

There is not a single executable command, code snippet, or invocation example; the JSON input schemas are concrete but nothing shows how to run anything. Critically, the eight documented scripts (keyword_analyzer.py, metadata_optimizer.py, etc.) do not exist in the bundle - no scripts/, references/, or assets/ directory is present - so the function inventories reference files Claude can never actually call. This is high-level description with the execution steps missing, matching anchor 2.

2 / 5

Workflow Clarity

The body is a capability catalog, not a sequenced process: no section gives a step-by-step workflow (e.g., research keywords -> optimize metadata -> validate character limits -> track rankings), and validation checkpoints are absent everywhere despite batch/destructive-adjacent operations like metadata overwrites. A rough implicit sequence (research, optimize, track) exists only at section level, matching anchor 2.

2 / 5

Progressive Disclosure

This is a monolithic ~400-line SKILL.md with zero external reference files, while content that clearly belongs in separate files - API docs for eight scripts, best-practice guides, output format specs - is fully inlined. Worse, the Scripts section points to files that are absent from the bundle, so the only 'references' are dangling. Anchor 2 (content that should be separate is inlined; references buried/broken) is the best fit.

2 / 5

Total

8

/

20

Passed

Description

65%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 solid, domain-specific description with good trigger vocabulary and a clear what, but it uses generic umbrella verbs instead of concrete capabilities and completely lacks a "Use when..." trigger clause, which caps completeness. Adding an explicit when-clause and naming concrete operations (keyword research, metadata optimization, review analysis) would lift it substantially.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user mentions app store visibility, app keywords, store listing optimization, or wants more app downloads.'

Replace umbrella verbs ('researching, optimizing, and tracking') with concrete capabilities: 'Research app keywords, optimize titles/descriptions/keyword fields, analyze competitor listings, and track keyword rankings.'

Drop the 'Complete ... toolkit' framing; it reads as an over-claim and adds no trigger value.

DimensionReasoningScore

Specificity

The description names the domain clearly ("App Store Optimization (ASO)", "Apple App Store and Google Play Store") with three actions ("researching, optimizing, and tracking mobile app performance"), but those are broad umbrella verbs rather than concrete operations, and "Complete ... toolkit" is mild buzzword padding. It sits between anchor 3 (domain plus 1-2 actions, not comprehensive) and anchor 4 (several specific actions), but the generic verbs keep it closer to 3.

3 / 5

Completeness

The "what" is clear (research, optimize, and track mobile app performance on both stores), but there is no "Use when..." clause or equivalent trigger guidance, which caps this dimension at 3 per the judging guidelines. It is not 2 because the "what" half is specific and well-stated, not vague.

3 / 5

Trigger Term Quality

Includes the natural terms users would say: "App Store Optimization", the "(ASO)" synonym, "Apple App Store", "Google Play Store", and "mobile app performance". Not anchor 5 because common phrasings like "app keywords", "app ranking", "store listing", or "get more downloads" are missing.

4 / 5

Distinctiveness Conflict Risk

ASO for the two mobile app stores is a clear, well-defined niche with distinct trigger terms; it would not be confused with web SEO, general marketing, or document skills. Minor overlap with broad marketing skills exists but is minimal.

5 / 5

Total

15

/

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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/app-store-optimization/SKILL.md

Reviewed

Table of Contents

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