# Prioritize SEO Keywords and Topic Clusters

Keyword lists often lack reliable priorities, intent labels, and content direction. This skill scores available data and organizes opportunities into actionable clusters and calendars.

## Install

```bash
npx skillstore add aaron-he-zhu/keyword-research
```

## Metadata

- Status: approved
- Slug: aaron-he-zhu-keyword-research
- Version: 17.0.0
- Author version: 17.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: 341dabaf872f88b19bb9df9d19f1e2df7e1a4826017554529f13096a1a5a8c82
- Author: aaron-he-zhu
- GitHub username: aaron-he-zhu
- License: Apache-2.0
- Repository: https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/seo-geo/research/keyword-research
- Ref: d71c7417a35d5c2624161bd2fe8de8a41a362128
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network, filesystem
- Quality score: 78
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/aaron-he-zhu-keyword-research
- Manifest: https://skillstore.pages.dev/api/skills/aaron-he-zhu-keyword-research/manifest

## Capabilities

- Expands seed topics through product, problem, audience, industry, modifier, and long-tail patterns.
- Classifies keywords by informational, navigational, commercial, or transactional intent.
- Calculates opportunity scores from supplied volume, difficulty, and intent values.
- Labels metrics as measured, user-provided, estimated, or unavailable.
- Flags question, definition, comparison, list, and how-to queries for GEO planning.
- Groups priorities into pillar pages, cluster content, and a recommended publishing calendar.

## Use Cases

- Plan a New SEO Topic: Turn a seed topic into prioritized keywords, intent groups, and an initial content sequence.
- Find Revenue-Focused Opportunities: Rank commercial and transactional terms using available demand, difficulty, and business relevance signals.
- Build a Publishable Topic Cluster: Map a pillar page, supporting articles, internal links, and a practical release cadence.

## Prompt Templates

### Expand a Seed Topic

```
Research keywords for [topic] in [market and language]. Group ideas by search intent and label every metric by evidence source.
```

### Prioritize Product Keywords

```
Research [product or service] for [audience]. Prioritize quick wins, growth terms, and GEO opportunities using my supplied metrics: [metrics].
```

### Create a Topic Cluster

```
Build a topic cluster for [pillar topic]. Include primary and secondary keywords, intent, content format, internal links, and publishing order.
```

### Apply Advanced Opportunity Scoring

```
Score these keywords using volume, difficulty, intent, CPC, trend, current rank, and authority: [keyword data]. Explain impact and confidence separately.
```

## Limitations

- It cannot verify search volume or difficulty without connected tools or supplied data.
- Model estimates are directional and must not be treated as measured metrics.
- Competitor-relative coverage analysis belongs in a separate content-gap workflow.
- Optional live-data helpers depend on external services, availability, and usage policies.

## Best Practices

- Provide audience, market, language, business goal, domain strength, and trusted metrics before scoring.
- Verify intent against current search results when live data is available.
- Refresh priorities quarterly and after meaningful ranking, product, or market changes.

## Anti Patterns

- Do not present inferred volume, difficulty, or trends as measured data.
- Do not prioritize high volume without checking intent, relevance, and ranking feasibility.
- Do not create thin cluster pages when one stronger page can satisfy the same intent.

## Security Audit

- Audited at: 2026-07-12T12:38:14.528\+00:00
- Summary: Most alerts are false positives caused by Markdown code fences, inline code, documentation links, and repository metadata. Three findings are confirmed because the instructions execute external Python connectors that contact third-party services. No prompt injection or malicious intent was found.

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