keyword-research

keyword-research is a skill for Claude Code from Eronred/aso-skills. It costs 75 tokens per session (1,214 once invoked), scanned A, original, MIT.

An App Store keyword research guide for finding search terms people may use to discover an app. It examines suggestions and competing apps to build a prioritized keyword strategy.

In plain words
What is it for?
Use it to expand seed keywords, review competitor rankings, identify lower-competition opportunities, and choose keywords for downloads, revenue, or brand awareness in a target country.
Why use it?
It removes the uncertainty of choosing which words to target in an app's store listing. It helps reveal longer, more specific searches and gaps between an app and its competitors.

Skill for Claude Code

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

Part of the aso-skills plugin — 40 skills shipped together

Good fit Use it to expand seed keywords, review competitor rankings, identify lower-competition opportunities, and choose keywords for downloads, revenue, or brand awareness in a target country.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/eronred/aso-skills/keyword-research
About the project

ASO & App Marketing Skills is a collection of AI-agent skills for improving mobile-app discoverability and marketing through keyword research, metadata optimization, competitor analysis, and market data. It is for indie developers, app marketers, and growth teams using compatible coding agents, and the catalogue contains the skills and instructions they use.

Eronred/aso-skills · 1,851 stars · on GitHub · appeeky.com

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 Eronred/aso-skills --skill keyword-research
Clone the repo
git clone --depth 1 https://github.com/Eronred/aso-skills

Made for: Claude Code.

Or install aso-skills, the plugin that ships this one along with the rest of its 40 skills.

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 keyword-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/eronred/aso-skills/keyword-research/github.svg)](https://agentmods.dev/skills/eronred/aso-skills/keyword-research)
Your own site
<a href="https://agentmods.dev/skills/eronred/aso-skills/keyword-research"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/keyword-research/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 keyword-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/eronred/aso-skills/keyword-research"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/keyword-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,214 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. Third-party audits
  • Socket pass 18 Mar 2026
  • Snyk warn 28 Feb 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00075 $0.01214
Opus 5 $0.00037 $0.00607
Sonnet 5 $0.00015 $0.00243
Haiku 4.5 $0.00007 $0.00121

Measured 12d ago against content hash fb938fd60bf6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

keyword-research 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 12d 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/keyword-research/SKILL.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword Research

You are an expert ASO keyword researcher with deep knowledge of App Store search behavior, keyword indexing, and ranking algorithms. Your goal is to help the user discover high-value keywords and build a prioritized keyword strategy.

Initial Assessment

  1. Check for app-marketing-context.md — read it for app context, competitors, and goals
  2. Ask for the App ID (to understand current rankings)
  3. Ask for target country (default: US)
  4. Ask for seed keywords — 3-5 words that describe the app's core function
  5. Ask about intent: Are they optimizing for downloads, revenue, or brand awareness?

Research Process

Phase 1: Seed Expansion

Start with the user's seed keywords and expand using multiple methods:

Apple Search Suggestions

  • Use each seed keyword to get autocomplete suggestions
  • Try variations: "[keyword] app", "[keyword] for [audience]", "best [keyword]"
  • Note long-tail suggestions — these often have lower competition

Competitor Keywords

  • Pull keyword rankings for top 3-5 competitors
  • Identify keywords competitors rank for that the user doesn't
  • Look for keywords where competitors rank poorly (opportunity)

Category Analysis

  • What keywords do top apps in the category target?
  • Are there category-specific terms the user is missing?

Synonym & Related Terms

  • Generate synonyms and related terms for each seed keyword
  • Consider how users actually describe the problem (not the solution)
  • Think about misspellings and abbreviations users might search

Phase 2: Keyword Evaluation

For each keyword candidate, evaluate:

Signal What to check Why it matters
Search Volume Volume score (1-100) or traffic estimate Higher volume = more potential impressions
Difficulty Competition score (1-100) Lower difficulty = easier to rank
Relevance How closely it matches the app's function Irrelevant traffic doesn't convert
Intent Is the searcher looking to download? "how to edit photos" vs "photo editor app"
Current Rank Where the app currently ranks (if at all) Easier to improve existing rank than start from zero

Read the full file on GitHub · 142 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. 12d ago First seen · 142 lines · 75 tokens per session scan A fb938fd60bf6

Subscribe to this mod's changes

keyword-research is a skill published in the GitHub repository Eronred/aso-skills (1,851 stars, last pushed 20d ago), licensed MIT. It adds 75 tokens to every session and 1,214 once invoked, about $0.0004 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 2026-08-30.

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