aso

aso is a skill for Claude Code from anhnguyen0905/codex-mcp. It costs 90 tokens per session (1,211 once invoked), scanned A, original, MIT.

Guidance for improving an app's listing in the Apple App Store or Google Play so more people can find it and install it. ASO, or app store optimization, covers searchable text as well as the screenshots, icon, and videos that persuade visitors.

In plain words
What is it for?
Use it to research keywords, write titles and descriptions, plan store metadata, improve icons and screenshots, create preview videos, and measure listing conversion.
Why use it?
It separates discoverability from conversion: metadata affects which searches can show the app, while page content affects whether visitors install it. This makes it easier to diagnose falling installs.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the codex-flow plugin — 61 skills, 1 command, 1 MCP server shipped together

Good fit Use it to research keywords, write titles and descriptions, plan store metadata, improve icons and screenshots, create preview videos, and measure listing conversion.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anhnguyen0905/codex-mcp/aso
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add anhnguyen0905/codex-mcp --skill aso
Clone the repo
git clone --depth 1 https://github.com/anhnguyen0905/codex-mcp

Made for: Claude Code.

Or install codex-flow, the plugin that ships this one along with the rest of its 61 skills, 1 command, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for aso

README.md
[![agentmods](https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/aso/github.svg)](https://agentmods.dev/skills/anhnguyen0905/codex-mcp/aso)
Your own site
<a href="https://agentmods.dev/skills/anhnguyen0905/codex-mcp/aso"><img src="https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/aso/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for aso

Your own site · 80×15
<a href="https://agentmods.dev/skills/anhnguyen0905/codex-mcp/aso"><img src="https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/aso.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,211 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.01211
Opus 5 $0.00045 $0.00606
Sonnet 5 $0.00018 $0.00242
Haiku 4.5 $0.00009 $0.00121

Measured 9d ago against content hash e4b7e6119dae, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

aso scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/aso/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ASO (store listing discoverability and conversion)

The two jobs, kept separate

installs    = impressions × store-page CVR (impression → install)
impressions ≈ search/browse/referral traffic won by relevance and ranking

Metadata mostly moves impressions — which queries you can appear for at all. Creatives mostly move CVR — whether that traffic converts. Diagnose which half moved first: installs falling with CVR flat is a traffic problem, installs falling with impressions flat is a page problem. Paid traffic lands on the same page, so a CVR win compounds across all UA spend.

Metadata fields and what each affects

  • Apple App Store: app name, subtitle and the character-limited keyword field are indexed for search; the description is not, so it is purely a conversion asset. No repetition across fields, no wasted comma spacing, no plural duplicates. IAP and developer names also carry indexing weight.
  • Google Play: title, short description and long description are all indexed, so the long description carries real search weight — but users read it, so stuffing costs conversion; natural repetition of the priority term beats a keyword list.
  • Both: title and the first line of subtitle/short description are the highest-leverage text — what a browsing user reads before deciding.

Keyword research: relevance before volume

Build the term set from real query sources — store autosuggest, competitor listings, search-term reports from paid app campaigns, support tickets, category vocabulary. Triage each term on relevance to what the app actually does, estimated volume, and difficulty (who ranks now, how entrenched). Prefer ranking well for a moderate-volume term you genuinely satisfy over placing low on a head term: irrelevant traffic depresses CVR and the ranking signals that follow it. Track rank and installs per term — rank alone hides worthless traffic.

Creatives are the real conversion lever

The icon appears in every impression, so it gates result-list CTR as well as page CVR and must read at thumbnail size. Screenshots: the first one or two are all most users see — lead with the single strongest value message, text legible small, promise consistent with the product or you buy churn instead of retention. A preview/promo video can lower CVR as easily as raise it depending on its first seconds; test it, never assume.

Read the full file on GitHub · 93 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 93 lines · 90 tokens per session scan A e4b7e6119dae

Subscribe to this mod's changes

aso is a skill published in the GitHub repository anhnguyen0905/codex-mcp (3 stars, last pushed yesterday), licensed MIT. It adds 90 tokens to every session and 1,211 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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