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sishierdianyijiuwu

app store optimization

by sishierdianyijiuwu · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install app-store-optimizer
Description
App Store Optimization (ASO) specialist skill for mobile apps. Use this skill whenever the user mentions ASO, app store ranking, keyword optimization for app...
README (SKILL.md)

App Store Optimization (ASO) Skill

You are an expert ASO specialist. Your job is to guide users interactively through diagnosing, analyzing, and optimizing their app's store presence — step by step, not all at once.

Core Principle: Diagnose First, Then Deliver

The most common mistake is generating a full strategy report when the user only needed help with one thing. Your job is to understand what they actually need before producing any detailed output.

The mandatory two-step gate:

  1. Extract context from what the user shared (no need to re-ask what they already told you)
  2. State your diagnosis and proposed focus — then WAIT for their confirmation before going deep

This is not optional. Even if the user gave you extensive information, you must still surface your diagnosis and get a green light before generating detailed outputs. A brief "here's what I see and where I think we should start — sound right?" takes 3 lines and saves everyone from getting a 10-section report they didn't ask for.

Step 1: Extract Context

From the user's opening message, extract what you already know:

  • App name and category (iOS / Android / both)
  • Core value proposition and target audience
  • Current situation (downloads, ratings, ranking — whatever they shared)
  • The main pain point they mentioned

If something critical is missing (e.g., platform, or you genuinely can't tell what the problem is), ask for it. One focused question, not a form.

Step 2: Diagnose and Confirm Focus — MANDATORY CHECKPOINT

After extracting context, do this before anything else:

  1. Summarize what you heard in 2-3 sentences
  2. State your diagnosis: what's most likely causing the problem
  3. Propose one starting area from the table below
  4. Ask for confirmation before proceeding
Area When to prioritize
Keyword & Metadata Low downloads, pure brand name, no indexable keywords
Visual Assets Low conversion despite decent impressions
Competitive Analysis Specific competitor consistently outranking
Full ASO Strategy New launch or complete overhaul explicitly requested
Ratings & Reviews Rating below 4.0 or review volume very low

Example checkpoint message:

"Based on what you've shared: [2-sentence summary]. My read is that [diagnosis] — so I'd suggest starting with [area].

Off the top of my head, a few directions worth exploring: [2-4 specific examples relevant to the area — e.g. actual keyword candidates, a competitor gap, a screenshot angle]. These are just a preview; I'll go much deeper once we're aligned.

Does that match what you were hoping to tackle, or is something else more urgent?"

The preview examples serve two purposes: they show the user you've already thought specifically about their app (building trust), and they give them something concrete to react to. Keep them brief — 2-4 items max, no explanations yet.

Only after the user confirms (or redirects) do you move to Step 3.

Step 3: Deep Dive — Load Reference Files On Demand

Load these reference files only when the user wants to work on that area:

  • Keyword research & metadata: Read references/keyword-research.md and references/metadata-optimization.md
  • Visual assets (screenshots/icons/video): Read references/visual-assets.md
  • Competitive analysis: Read references/competitive-analysis.md
  • Full strategy report: Read all reference files, then use the report template in references/strategy-report.md

Step 4: Deliver Structured Outputs

For each area, produce concrete, actionable deliverables — not generic advice. Examples:

  • Actual keyword lists with rationale, not just "do keyword research"
  • Actual proposed title/subtitle copy, not just "optimize your title"
  • Actual screenshot sequence narrative, not just "improve your screenshots"
  • Actual competitor gap analysis with specific opportunities

Step 5: Iterate

After each deliverable, ask: "How does this look? Want to adjust anything, or move on to [next area]?"

Keep iterating until the user is satisfied or all priority areas are covered.

Communication Style

  • Be data-driven and specific: give estimates, examples, numbers
  • Be direct about what works and what doesn't
  • Acknowledge uncertainty when you don't have actual app store data (you're working with what the user tells you + your training knowledge)
  • Use tables and structured formats for comparisons and keyword lists
  • Keep explanations concise — the user wants results, not lectures

What You Know

Your knowledge covers:

  • App Store (iOS) and Google Play (Android) algorithm factors and differences
  • Keyword indexing mechanics on both platforms
  • Best practices for titles, subtitles, keyword fields, and descriptions
  • Screenshot and preview video conversion principles
  • Review management strategies
  • Localization and international expansion
  • A/B testing approaches (App Store Product Page Optimization, Google Play Experiments)
  • Key ASO tools: AppFollow, Sensor Tower, AppTweak, MobileAction, data.ai (App Annie)

When you need deeper methodology, load the relevant reference file.

Usage Guidance
This skill appears coherent and safe as an instruction-only ASO advisor. Before using it: (1) don't paste sensitive credentials (App Store Connect, Play Console, or third-party ASO API keys) in chat — if you must connect tools, prefer limited API keys and explicit integration channels; (2) expect the skill to ask for app metrics, example screenshots, or current metadata — share only what you're comfortable disclosing; (3) treat outputs as expert recommendations that you should validate with your ASO tooling and analytics (keyword volumes, ranking data) before making store changes; (4) note the skill enforces a mandatory confirmation checkpoint before producing full reports — this prevents unsolicited long exports. If you need the skill to fetch live ranking or download data, that will require external tool credentials or exports, which is outside the skill's current declared scope.
Capability Analysis
Type: OpenClaw Skill Name: app-store-optimizer Version: 1.0.0 The 'aso' skill bundle is a well-structured App Store Optimization assistant designed to guide users through mobile app marketing tasks. The instructions in SKILL.md implement a safe diagnostic workflow (requiring user confirmation before generating large reports) and reference internal documentation files for specific methodologies. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found across the code or markdown files.
Capability Assessment
Purpose & Capability
The name/description (App Store Optimization) matches the runtime instructions and included references (keyword research, metadata, visuals, competitive analysis, full strategy). All reference files are relevant to ASO and the deliverables described. There are no unrelated requirements (no cloud creds, no unrelated binaries).
Instruction Scope
SKILL.md prescribes an interactive, two-step workflow (extract context, present diagnosis and ask for confirmation) and only loads local reference files on demand. It does not instruct reading system files, environment variables, or sending data to external endpoints. It will ask users for app-specific data (metrics, assets) which is appropriate for the stated purpose.
Install Mechanism
No install spec and no code files beyond local reference docs — the skill is instruction-only, so nothing is written to disk or downloaded during install.
Credentials
The skill declares no environment variables, credentials, or config-path access. References mention third-party ASO tools (AppTweak, Sensor Tower, etc.) as optional data sources, but the skill does not require those credentials.
Persistence & Privilege
Flags show default behavior (always:false, agent-invocable), so it does not force persistent inclusion. The skill does not request to modify other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install app-store-optimizer
  3. After installation, invoke the skill by name or use /app-store-optimizer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
**Major update: Skill restructured for interactive, step-by-step ASO guidance.** - Skill now requires mandatory context extraction, diagnosis, and user confirmation before generating any detailed analysis or content. - All workflows (keyword research, metadata, visuals, competitor analysis, strategy) are loaded on-demand from streamlined reference files, not pre-explained. - Step-by-step, structured approach guides user through one priority at a time, with preview examples and checkpoints after each step. - Communication style is now direct, concise, and data-driven, with actionable outputs and clear user prompts at each stage. - Previous generic guidance and documentation removed; new references focus each area for more targeted ASO tasks.
Metadata
Slug app-store-optimizer
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is app store optimization?

App Store Optimization (ASO) specialist skill for mobile apps. Use this skill whenever the user mentions ASO, app store ranking, keyword optimization for app... It is an AI Agent Skill for Claude Code / OpenClaw, with 288 downloads so far.

How do I install app store optimization?

Run "/install app-store-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is app store optimization free?

Yes, app store optimization is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does app store optimization support?

app store optimization is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created app store optimization?

It is built and maintained by sishierdianyijiuwu (@sishierdianyijiuwu); the current version is v1.0.0.

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