> Discover, analyze, and prioritize keywords for SEO and GEO content strategies from a seed keyword or niche. Identifies high-value opportunities based on search volume, competition, intent, and business relevance. Generates topic clusters. For building a dated editorial calendar from your own Search Console data, use `content-planner` instead — this skill is seed-driven keyword discovery, not calendar scheduling. Use when asked to "find keywords", "keyword research", "keyword analysis", "search volume", "keyword difficulty", "content ideas from a seed", or any keyword discovery task.
npx skills add https://github.com/nowork-studio/NotFair --skill keyword-research
Discovers, analyzes, and prioritizes keywords for SEO and GEO content strategies. Identifies high-value opportunities based on search volume, competition, intent, and business relevance.
Use this when the conversation involves any of these situations — even if the user does not use SEO terminology:
Use this whenever the task needs reusable market intelligence that should influence strategy, not just an ad hoc answer.
Start with one of these prompts.
Research keywords for [topic/product/service]
Find keyword opportunities for a [industry] business targeting [audience]
Find low-competition keywords for [topic] with commercial intent
Identify question-based keywords for [topic] that AI systems might answer
What keywords is [competitor URL] ranking for that I should target?
> Note: All integrations are optional. This skill works without any API keys — users provide data manually when no tools are connected.
With ~~SEO tool + ~~search console connected:
Automatically pull historical search volume data, keyword difficulty scores, SERP analysis, current rankings from ~~search console, and competitor keyword overlap. The skill will fetch seed keyword metrics, related keyword suggestions, and search trend data.
With manual data only:
Ask the user to provide:
Proceed with the full analysis using provided data. Note in the output which metrics are from automated collection vs. user-provided data.
When a user requests keyword research:
Ask clarifying questions if not provided:
Start with:
For each seed keyword, generate variations:
## Keyword Expansion Patterns
### Modifiers
- Best [keyword]
- Top [keyword]
- [keyword] for [audience]
- [keyword] near me
- [keyword] [year]
- How to [keyword]
- What is [keyword]
- [keyword] vs [alternative]
- [keyword] examples
- [keyword] tools
### Long-tail Variations
- [keyword] for beginners
- [keyword] for small business
- Free [keyword]
- [keyword] software/tool/service
- [keyword] template
- [keyword] checklist
- [keyword] guide
Categorize each keyword:
| Intent | Signals | Example | Content Type |
|--------|---------|---------|--------------|
| Informational | what, how, why, guide, learn | "what is SEO" | Blog posts, guides |
| Navigational | brand names, specific sites | "google analytics login" | Homepage, product pages |
| Commercial | best, review, vs, compare | "best SEO tools [current year]" | Comparison posts, reviews |
| Transactional | buy, price, discount, order | "buy SEO software" | Product pages, pricing |
Score each keyword (1-100 scale):
### Difficulty Factors
**High Difficulty (70-100)**
- Major brands ranking
- High domain authority competitors
- Established content (1000+ backlinks)
- Paid ads dominating SERP
**Medium Difficulty (40-69)**
- Mix of authority and niche sites
- Some opportunities for quality content
- Moderate backlink requirements
**Low Difficulty (1-39)**
- Few authoritative competitors
- Thin or outdated content ranking
- Long-tail variations
- New or emerging topics
Formula: Opportunity = (Volume × Intent Value) / Difficulty
Intent Value assigns a numeric weight by search intent:
### Opportunity Matrix
| Scenario | Volume | Difficulty | Intent | Priority |
|----------|--------|------------|--------|----------|
| Quick Win | Low-Med | Low | High | ⭐⭐⭐⭐⭐ |
| Growth | High | Medium | High | ⭐⭐⭐⭐ |
| Long-term | High | High | High | ⭐⭐⭐ |
| Research | Low | Low | Low | ⭐⭐ |
Keywords likely to trigger AI responses:
### GEO-Relevant Keywords
**High GEO Potential**
- Question formats: "What is...", "How does...", "Why is..."
- Definition queries: "[term] meaning", "[term] definition"
- Comparison queries: "[A] vs [B]", "difference between..."
- List queries: "best [category]", "top [number] [items]"
- How-to queries: "how to [action]", "steps to [goal]"
**AI Answer Indicators**
- Query is factual/definitional
- Answer can be summarized concisely
- Topic is well-documented online
- Low commercial intent
Group keywords into content clusters:
## Topic Cluster: [Main Topic]
**Pillar Content**: [Primary keyword]
- Search volume: [X]
- Difficulty: [X]
- Content type: Comprehensive guide
**Cluster Content**:
### Sub-topic 1: [Secondary keyword]
- Volume: [X]
- Difficulty: [X]
- Links to: Pillar
- Content type: [Blog post/Tutorial/etc.]
### Sub-topic 2: [Secondary keyword]
- Volume: [X]
- Difficulty: [X]
- Links to: Pillar + Sub-topic 1
- Content type: [Blog post/Tutorial/etc.]
[Continue for all cluster keywords...]
Produce a report containing: Executive Summary, Top Keyword Opportunities (Quick Wins, Growth, GEO), Topic Clusters, Content Calendar, and Next Steps.
> Reference: See references/example-report.md for the full report template and example.
> Reference: See references/example-report.md for a complete example report for "project management software for small businesses".
Map all keywords for [topic] by search intent and funnel stageIdentify seasonal keyword trends for [industry]What keywords do [competitor 1], [competitor 2] rank for that I'm missing?Research local keywords for [business type] in [city/region]A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
Take nowork-studio/keyword-research from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.