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keyword-research · appeeky — Claude Code skill: what it does, how to install

Discovers and prioritizes App Store keywords, scores ranking opportunities, and maps search terms into app metadata fields.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add appeeky/aso-skills --skill keyword-research -a claude-code
Open on GitHub

What keyword-research does

This skill collects and prioritizes App Store search queries. First, the agent reads app-marketing-context.md, then requests the App ID, 3 to 5 seed keywords, target country (defaulting to US), and campaign intent: downloads, revenue, or brand awareness. It expands seeds through Apple Search autocomplete suggestions, top 3-5 competitor rankings, and category terms.

Candidate keywords are scored from 1 to 100 across volume, difficulty, and relevance. The skill computes an Opportunity Score using the exact formula (Volume × 0.4) + ((100 - Difficulty) × 0.3) + (Relevance × 0.3). The resulting terms are divided into primary keywords for the 30-character title, secondary terms for the 30-character subtitle, and long-tail terms for the 100-character keyword field without spaces after commas.

Relevance scoring requires manual assessment, because keyword viability depends strictly on your app's actual feature set. The final report gives a competitor keyword gap table and tactical recommendations.

What it helps with

  • expand seed keywords using Apple autocomplete and competitor rankings
  • calculate an opportunity score for candidate search terms
  • allocate keywords across title, subtitle, and keyword field limits
  • identify keyword ranking gaps against 3-5 competitor apps

Example prompts for the agent

  • Run keyword research for my app, here is the App ID and 3 seed keywords
  • Find keywords for the US App Store and calculate the opportunity score
  • Identify competitor keyword gaps and group terms into title and subtitle

How to install keyword-research

1Skills CLI (Vercel)

npx skills add appeeky/aso-skills --skill keyword-research -a claude-code

2Manually: put the files in place

~/.claude/skills/keyword-research/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/keyword-research/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about keyword-research

How do I install keyword-research in Claude Code?

Run npx skills add appeeky/aso-skills --skill keyword-research -a claude-code in your terminal.

What does the keyword-research skill do?

It expands App Store search terms, evaluates volume, difficulty, and relevance, and outputs a prioritized metadata distribution strategy.

How is the keyword opportunity score calculated?

The skill applies the formula Opportunity = (Volume × 0.4) + ((100 - Difficulty) × 0.3) + (Relevance × 0.3) on a 1-100 scale for each parameter.

Source text

SKILL.md · MIT
---
name: keyword-research
description: When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.
metadata:
  version: 1.0.0
---

# 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 |

### Phase 3: Opportunity Scoring

Calculate an **Opportunity Score** for each keyword:

```
Opportunity = (Volume × 0.4) + ((100 - Difficulty) × 0.3) + (Relevance × 0.3)
```

Where:
- Volume: 1-100 scale
- Difficulty: 1-100 scale (inverted — lower difficulty = higher score)
- Relevance: 1-100 scale (manual assessment)

### Phase 4: Keyword Grouping

Group keywords into strategic buckets:

**Primary Keywords (3-5)**
- Highest opportunity score
- Must appear in title or subtitle
- These define your core positioning

**Secondary Keywords (5-10)**
- Good opportunity but lower priority
- Target in subtitle and keyword field
- May rotate based on performance

**Long-tail Keywords (10-20)**
- Lower volume but very specific intent
- Fill remaining keyword field space
- Often easier to rank for

**Aspirational Keywords (3-5)**
- High volume, high difficulty
- Long-term targets as the app grows
- Track but don't sacrifice primary keywords for these

## Output Format

### Keyword Research Report

**Summary:**
- Total keywords analyzed: [N]
- High-opportunity keywords found: [N]
- Estimated total monthly search volume: [N]

**Top Keywords by Opportunity:**

| Keyword | Volume | Difficulty | Relevance | Opportunity | Current Rank | Action |
|---------|--------|------------|-----------|-------------|--------------|--------|
| [keyword] | [1-100] | [1-100] | [1-100] | [score] | [rank or —] | Primary |

**Keyword Strategy:**

```
Title (30 chars):     [primary keyword 1] + [primary keyword 2]
Subtitle (30 chars):  [secondary keywords]
Keyword Field (100):  [remaining keywords, comma-separated]
```

**Competitor Keyword Gap:**

| Keyword | Your Rank | Competitor 1 | Competitor 2 | Competitor 3 | Gap? |
|---------|-----------|-------------|-------------|-------------|------|

**Recommendations:**
1. Immediate changes to make
2. Keywords to start tracking
3. Content/feature opportunities based on keyword demand

## Tips for the User

- **Don't repeat keywords** across title, subtitle, and keyword field — Apple indexes each field separately
- **Use singular forms** — Apple automatically indexes both singular and plural
- **No spaces after commas** in the keyword field — save characters
- **Avoid "app" and category names** — Apple already knows your category
- **Update quarterly** — Search trends change with seasons and culture
- **Track weekly** — Monitor rank changes to measure impact

## Related Skills

- `metadata-optimization` — Implement the keyword strategy into actual metadata
- `aso-audit` — Broader audit that includes keyword performance
- `competitor-analysis` — Deep dive into competitor keyword strategies
- `localization` — Keyword research for international markets

© appeeky · MIT · appeeky/aso-skills

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