Name: app-store-optimization
Rating: 61.2 (1 reviews)
Author: administrakt0r

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

42%

Does it follow best practices?

Impact

94%

1.22x

Average score across 3 eval scenarios

Securityby

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

Quality

Content

31%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 well-sectioned and informative but over-long and monolithic: it relies on repetitive boilerplate prompts, describes scripts that are not actually bundled, and provides no executable code. Splitting content into reference files and adding real script implementations would substantially improve it.

Suggestions

Actually bundle the eight referenced Python scripts in a scripts/ directory with full implementations, or remove the per-function listings if the scripts are not provided.

Move the capability lists, best practices, and per-task input/output schemas into reference files (e.g. references/best-practices.md, references/input-formats.md) and link to them one level deep from SKILL.md.

Replace the seven repeated 'Hey Claude—I just added the skill…' examples with a single concise usage example and remove padding that restates ASO concepts Claude already knows.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose: seven near-identical 'Hey Claude—I just added the skill…' boilerplate prompts and broad capability bullet-lists enumerate ASO basics Claude already knows rather than adding novel guidance.	2 / 5
Actionability	JSON input/output schemas and character-limit specs are concrete, but the eight referenced .py scripts are only listed by function name with no implementation and do not exist as bundled files, so nothing is executable.	2 / 5
Workflow Clarity	Input-to-output mappings and a launch checklist with verification items provide a rough sequence, but there are no explicit validation feedback loops (validate → fix → retry) across the optimization workflows.	3 / 5
Progressive Disclosure	The skill is a monolithic 400-line file with eight scripts and extensive best-practice content inlined that clearly belong in separate bundled files, and no references/, scripts/, or assets/ directories exist.	2 / 5
	Total	9 / 20 Passed

Description

53%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.

The description clearly states what the skill does and targets a distinct niche, but it lacks an explicit 'Use when...' trigger clause and relies on generic action verbs rather than concrete capabilities. Adding natural trigger phrases and more specific actions would raise it.

Suggestions

Add an explicit 'Use when...' clause with concrete trigger phrases, e.g. 'Use when optimizing app store listings, researching ASO keywords, or tracking app rankings on the Apple App Store or Google Play Store.'

Replace generic verbs ('researching, optimizing, and tracking') with specific concrete actions like 'research keyword volume, optimize titles and descriptions within character limits, and track keyword rankings'.

Include natural synonyms users say such as 'app store ranking', 'app keywords', and 'app listing' to improve trigger term coverage.

Dimension	Reasoning	Score
Specificity	Names the ASO domain and three actions ('researching, optimizing, and tracking'), but these are generic verbs rather than concrete specific operations, so coverage is not comprehensive enough for a 4.	3 / 5
Completeness	The 'what' is clearly stated (a complete ASO toolkit for researching/optimizing/tracking), but there is no 'Use when...' trigger clause; per the rubric a missing explicit trigger caps completeness at 3.	3 / 5
Trigger Term Quality	Includes relevant terms ('App Store Optimization', 'ASO', 'Apple App Store', 'Google Play Store') but omits common natural phrases users actually say like 'app store ranking', 'app keywords', or 'app listing'.	3 / 5
Distinctiveness Conflict Risk	ASO for the Apple and Google mobile stores is a clear, specific niche with minimal conflict risk, though there is minor overlap with general marketing/SEO skills.	4 / 5
	Total	13 / 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: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/app-store-optimization/SKILL.md
Commit: 900c504

Reviewed: 7 hours ago

Table of Contents

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