Skills app-store-optimization
📦

app-store-optimization

Content revision r2 Safe 📁 Filesystem access🌐 Network access⚙️ External commands

Optimize Mobile App Store Performance

Mobile teams often lack a clear process for improving app discovery and store conversion. This skill produces prioritized metadata, keyword, testing, localization, review, and launch recommendations.

Supports: Claude Codex Code(CC)
🥉 78 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "app-store-optimization" from https://skillstore.io/skills/sickn33-app-store-optimization.md and its manifest at https://skillstore.io/api/skills/sickn33-app-store-optimization/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/sickn33-app-store-optimization.md Signed manifest GET /api/skills/sickn33-app-store-optimization/manifest Signed lockfile GET /api/skills/sickn33-app-store-optimization/lockfile

Test it

Using "app-store-optimization". Apple listing for FocusFlow with a 34-character title and three supplied priority keywords.

Expected outcome:

  • Title issue: the current title exceeds Apple's stated 30-character limit.
  • Recommended title: FocusFlow: Daily Tasks.
  • Priority: test the shorter title before revising secondary metadata.

Using "app-store-optimization". Two hundred supplied reviews for a fitness app, including ratings and dates.

Expected outcome:

  • Sentiment trend: negative feedback is concentrated in recent sync failures.
  • Top request: offline workout access.
  • Recommended action: address sync reliability before promoting new features.

Using "app-store-optimization". Icon test with baseline conversion, expected lift, daily traffic, and significance target.

Expected outcome:

  • Primary metric: store listing conversion rate.
  • Run both variants concurrently until the planned sample is reached.
  • Adopt the variant only when the defined significance and minimum lift thresholds are met.

Security Audit

Safe
v5 • 7/23/2026 Open versioned report

All 90 static findings are false positives caused by ASO prose, Markdown formatting, standard installation paths, and the noun "requests." Reviewed contexts show no network client, shell execution, hidden-file harvesting, system reconnaissance, or prompt injection.

13
Files scanned
6,089
Lines analyzed
0
Review items
0
False positives ignored

Risk Factors

📁 Filesystem access (5)
README.md:189 README.md:204 README.md:181 README.md:189 README.md:204
🌐 Network access (7)
review_analyzer.py:3 review_analyzer.py:270 review_analyzer.py:596 review_analyzer.py:637 SKILL.md:290 SKILL.md:361 SKILL.md:362
⚙️ External commands (50)
SKILL.md:76-84 SKILL.md:84-87 SKILL.md:87-104 SKILL.md:104-107 SKILL.md:107-115 SKILL.md:115-118 SKILL.md:118-138 SKILL.md:138-194 SKILL.md:194-196 SKILL.md:196-199 SKILL.md:199-201 SKILL.md:201-204 SKILL.md:204-206 SKILL.md:206-209 SKILL.md:209-211 SKILL.md:211-214 SKILL.md:214-216 SKILL.md:216-219 SKILL.md:219-221 SKILL.md:221-224 SKILL.md:224-226 SKILL.md:226-234 SKILL.md:234-235 SKILL.md:235-236 SKILL.md:236-237 SKILL.md:237-243 SKILL.md:243-244 SKILL.md:244-245 SKILL.md:245-246 SKILL.md:246-247 SKILL.md:247-253 SKILL.md:253-254 SKILL.md:254-255 SKILL.md:255-256 SKILL.md:256-262 SKILL.md:262-263 SKILL.md:263-264 SKILL.md:264-265 SKILL.md:265-266 SKILL.md:266-267 SKILL.md:267-273 SKILL.md:273-274 SKILL.md:274-275 SKILL.md:275-276 SKILL.md:276-277 SKILL.md:277-283 SKILL.md:283-284 SKILL.md:284-285 SKILL.md:285-286 SKILL.md:286-287
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
Share & cite this report

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Open versioned report
Security Assessment

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Academic citations (APA · BibTeX · CFF)

APA citation

sickn33. (2026). app-store-optimization security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-app-store-optimization/audits/5

BibTeX citation

@techreport{sickn33-sickn33-app-store-optimization-2026, author = {sickn33}, title = {app-store-optimization security audit report (audit version 5)}, institution = {Skillstore}, year = {2026}, number = {5}, url = {https://skillstore.io/skills/sickn33-app-store-optimization/audits/5}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "app-store-optimization security audit report (audit version 5)" version: "unspecified" type: report authors: - name: "sickn33" date-released: "2026-07-23" url: "https://skillstore.io/skills/sickn33-app-store-optimization/audits/5" identifiers: - type: other value: "skillstore:sickn33-app-store-optimization:audit:5" description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Recently maintained
sickn33 Recommended Current

sickn33-app-store-optimization

Skillstore Score 78
Evidence Confidence High
Skillstore usage 12
Updated

2026-08-21

alirezarezvani

alirezarezvani-app-store-optimization

Skillstore Score 78
Evidence Confidence High
Skillstore usage 12
Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High
55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance

What You Can Build

Improve an Indie App Listing

Audit supplied keywords and metadata, then prioritize changes that can improve organic discovery and conversion.

Manage a Mobile Growth Program

Compare listings, review trends, and experiments across releases to guide an evidence-based ASO roadmap.

Prepare a Store Launch

Create platform checklists, localized metadata plans, and launch timing recommendations before submission.

Try These Prompts

Review One Listing 
Review this [platform] listing for [app name]. Check character limits, clarity, keyword placement, and conversion messaging, then prioritize five improvements.
Choose Target Keywords 
Analyze these candidate keywords using the supplied volume, competition, relevance, and ranking data. Recommend primary, secondary, and long-tail targets with reasons.
Compare Competitors and Reviews 
Compare our listing with these competitor listings and analyze the supplied reviews. Identify keyword gaps, recurring issues, feature requests, and three strategic opportunities.
Build an ASO Experiment Roadmap 
Using our metadata, ratings, conversion metrics, keyword rankings, and traffic, calculate an ASO score. Design two prioritized A/B tests with sample requirements and decision rules.

Best Practices

  • Provide current, platform-specific data and identify which metrics are measured or estimated.
  • Review generated metadata for factual accuracy, brand voice, and current store requirements.
  • Change one major test variable at a time and define success criteria before launch.

Avoid

  • Do not treat estimated search volume or ROI as verified platform data.
  • Do not copy competitor keywords without confirming relevance to actual app features.
  • Do not publish generated translations without native-speaker and policy review.

Frequently Asked Questions

Does this skill collect live store data?
No. It analyzes data you provide and can reference optional external research resources.
Which stores are supported?
The workflows cover Apple App Store and Google Play metadata, scoring, testing, localization, reviews, and launch planning.
Can it guarantee higher rankings?
No. Store algorithms are proprietary, and outcomes depend on competition, product quality, traffic, ratings, and changing policies.
Can it translate store metadata?
It can generate localization drafts and market guidance. A native speaker should validate every translation before publication.
Does it manage paid advertising?
No. The skill focuses on organic store discovery and conversion, not Apple Search Ads or Google Ads.
What inputs produce the best results?
Provide current metadata, target keywords, competitor listings, reviews, ratings, conversion metrics, rankings, platform, locale, and business goals.

Developer Details

Author

sickn33

License

MIT

Skillstore revision

r2

Version notice

The author did not declare a version.

Repository

https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/app-store-optimization

Ref

ebdfe608f5de2b66ff37ab4af12af8ac4f5e8006

Maintenance freshness

7/26/2026

Usage

10 downloads · 117 views

File structure

📄 ab_test_planner.py

📄 aso_scorer.py

📄 competitor_analyzer.py

📄 expected_output.json

📄 HOW_TO_USE.md

📄 keyword_analyzer.py

📄 launch_checklist.py

📄 localization_helper.py

📄 metadata_optimizer.py

📄 README.md

📄 review_analyzer.py

📄 sample_input.json

📄 SKILL.md

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