keyword-research
Guides keyword research for SEO: finding target keywords, assessing difficulty, understanding search intent, and building topical maps. ~95% of keywords get fewer than 10 searches/month; low-volume, high-intent terms often yield faster rankings and conversion.
Works with
6
total installs
6
this week
309
GitHub stars
0
upvotes
Install Skill
Run in your terminal
6
installs
6
this week
309
stars
Installation Guide
How to use keyword-research on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
keyword-research
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches keyword-research from kostja94/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate keyword-research. Access via /keyword-research in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
SEO Content: Keyword Research
Guides keyword research for SEO: finding target keywords, assessing difficulty, understanding search intent, and building topical maps. ~95% of keywords get fewer than 10 searches/month; low-volume, high-intent terms often yield faster rankings and conversion.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Initial Assessment
Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for product, audience, and positioning.
Identify:
- Product/service: What you offer
- Audience: Who searches for it
- Goals: Traffic, conversions, brand
- Tool access: Google Keyword Planner, Google Trends, or SEO tools
Discovery Methods
Base Discovery
| Method | Purpose |
|---|---|
| User perspective | What pain points? What would they search? Customer language from product context |
| Tool expansion | Related keywords, questions, suggestions; Google autocomplete, PAA, Related Searches |
| Competitor reverse | Analyze competitor titles, H1, URL; identify topics they rank for; find gaps (#4–10 = opportunity) — see competitor-research |
| Google PAA | People Also Ask and Related Searches; high-value signals from real user behavior |
| Extract from article | When auditing existing content: extract seed keywords from title, H1, H2s, meta keywords, first 100 words; then search "[primary keyword]" or "[primary keyword] related keywords" for opportunities; use "[primary keyword]" site:competitor.com if competitors known |
Google Autocomplete (Long-Tail Discovery)
Google autocomplete reflects real user searches; suggestions only appear if queries have actual traffic. Free; often uncovers low-volume long-tail that keyword tools miss. ~70% of search traffic is long-tail; lower competition, higher conversion.
Alphabet method (seed + space + letter):
- Type seed keyword + space + each letter:
keyword a,keyword b, ...keyword z - Record relevant suggestions; repeat with numbers 0-9
- Example:
SEO a-> "SEO audit," "SEO agency";SEO b-> "SEO basics," "SEO best practices"
Position variants (seed in different positions):
- Prefix:
a keyword,b keyword(discover what users add before) - Suffix:
keyword a,keyword b(most common; alphabet method) - Middle:
how to keyword a,best keyword for(question + modifier combos)
Question modifiers:
how to keyword,what is keyword,why keyword,when to keyword,keyword vskeyword for beginners,keyword for small business,keyword without
Why it works: Keyword tools filter low-volume terms; autocomplete only shows queries with real traffic. Use with PAA and Related Searches for full coverage. Categorize results by intent (informational, commercial, transactional).
Incremental Discovery
- User feedback: Support, community, reviews, NPS—high-frequency questions = unmet search demand
- Multi-platform search: Reddit, Quora, X (Twitter), Hacker News—real questions and discussions
Search Intent
| Intent | Content type | Example |
|---|---|---|
| Informational | Blog, guide, FAQ | "how to optimize sitemap" |
| Navigational | Brand page | "alignify login" |
| Commercial | Comparison, review | "SEO tools comparison" |
| Transactional | Product, pricing | "best SEO tool pricing" |
Intent Identification
Modifier words (often signal intent):
| Intent | Modifiers |
|---|---|
| Informational | "how," "what," "why," "guide," "tutorial" |
| Commercial | "best," "compare," "vs," "review," "top" |
| Transactional | "buy," "price," "cheap," "coupon," "free shipping" |
| Local | Location names |
SERP check: Search the term—knowledge cards/Wiki → informational; product lists/reviews → commercial; brand sites → navigational. Broader terms often show mixed SERP. See serp-features for feature types.
Long-Tail Expansion
- Google Autocomplete: Alphabet method, position variants, question modifiers; see above. Primary source for long-tail.
- Intent modifiers: Core + "how," "best," "vs," "compare," "price"
- Question words: "how to," "what is," "why," "when"
- Functional modifiers: Core + "-er/-or" (e.g., "image optimizer" for tool-type queries); often higher conversion
- Clustering: Group by SERP overlap (same top pages), semantic similarity, or intent.
Keyword Clustering & Topical Map
| Method | Use |
|---|---|
| SERP overlap | Keywords with overlapping top-ranking pages → same cluster |
| Semantic | Group by meaning, LSI, related concepts |
| Intent-based | Group by intent; separate pages if intent differs within cluster |
Pillar–cluster (map keywords to structure):
- Pillar (Hub): Broad topic page; links to clusters
- Cluster (Spoke): Focused subtopic; links back to pillar
- Target long-tail first; then pillar. Interlink clusters within topic.
- See content-strategy for full pillar-cluster planning and implementation.
Evaluate & Screen
| Factor | Consider |
|---|---|
| Search volume | Monthly searches; ~100+/month typical floor; niche can relax |
| Keyword difficulty (KD) | New sites target lower KD |
| CPC | Higher CPC often = stronger commercial intent |
| SERP features | Featured Snippet, PAA, zero-click; SERP features can satisfy intent without click—affects real traffic; see serp-features (Zero-Click section), featured-snippet |
| Screening order | 1) Remove irrelevant 2) Filter very low volume 3) Assess achievability 4) Prioritize commercial/transactional |
Product Positioning Test (SEO Fit)
Test if positioning is clear enough for search:
- XXX + Function words: Generator, Creator, Maker, Builder, Changer, Shortener, Scraper, Converter, Downloader, Translator, Extender, Summarizer, Resizer, Remover, Extractor, Recorder, Rewriter, Solver, Calculator; or Platform, Tool, Software, App, Provider, Assistant, Copilot
- Input + to + Output: e.g., "image to video," "text to speech"—clear input/output signals intent
Agent/Copilot products: Pure native Agent hard to grow via SEO; users rarely search "agent." Release related features first (e.g., CRM, sales bot for sales agent) to build traffic, then funnel to Agent product.
Principles
- Core rule: Someone must search it—validate with tools; avoid inventing terms
- Functional keywords: Tool-type (-er/-or) often convert better; users are closer to action
- Multi-language: Re-research in target language; don't translate existing lists. See translation for translation workflow.
SEO–PPC Keyword Synergy
Keyword research serves both SEO and Google Ads. Align both channels to avoid duplication, cannibalization, and wasted spend.
| Data flow | Use |
|---|---|
| keyword-research → google-ads | Keyword list, clusters, intent; support terms (login, forum, pricing) → negative keywords for PPC |
| google-ads → keyword-research | PPC conversion rate, Search Terms report → SEO priority; high-converting PPC terms = worth ranking organically |
| keyword-research → landing-page | Clusters → dedicated LP per intent; PAA questions → FAQ sections |
| GSC organic rank 4+ | If you rank well organically, consider reducing/pausing PPC on those terms to avoid cannibalization |
PPC data for SEO priority: SEO ROI ≈ (Organic clicks × PPC conversion rate × Customer value) − SEO cost. Use PPC conversion data to validate which keywords to pursue in organic.
Reference: Backlinko – SEO and PPC: 8 Smart Ways to Align
Data Sources
| Source | Use |
|---|---|
| Ahrefs | Keywords Explorer, Site Explorer |
| SEMrush | Keyword Overview, Organic Research |
| GSC | Search queries, impressions, clicks |
| GA | Traffic by landing page |
| PostHog | Feature/search usage |
Report Workflow
- Parse — Read Excel/CSV, infer keyword, volume, KD, intent, etc. from headers
- Enrich — Web search, visit competitor/product pages; read
project-context.mdif present - Build — Structure data for report
- Generate — Output report in chosen format
Output Format
- Keyword list with volume, KD, intent
- Keyword mapping to pages/content
- Content gaps (competitors rank, you don't)
- Priority ranking for implementation
- Topical map (cluster → pillar → page mapping)
Report Structure Reference
| Section | Content |
|---|---|
| Executive Summary | Priorities (top 3) |
| Keyword Overview | Total keywords, primary intent, avg KD, content gaps count |
| Keyword List | Keyword, volume, KD, intent, priority, target page |
| Keyword Mapping | Page/URL, target keywords, status |
| Content Gaps | Keywords competitors rank for that you don't |
| Action Plan | Priority, action, impact, effort |
| Appendix | Search intent reference (Informational, Commercial, Transactional, Navigational) |
Related Skills
- seo-strategy: SEO workflow, Product-Led SEO, audit approach; keyword research is Content phase
- google-ads: Keywords inform Search targeting; PPC data feeds back into SEO priority
- paid-ads-strategy: When to use paid vs organic; channel selection
- content-strategy: Keywords inform content plan; topic clusters
- content-optimization: Keyword placement, density vs stuffing, H2 keywords
- title-tag, meta-description: Keywords in title, description
- heading-structure: Keywords in H1, H2
- link-building: Keywords inform link targets
- serp-features: SERP features in keyword screening; PAA, Featured Snippet
- featured-snippet: Snippet-worthy query targeting
- competitor-research: Competitor keyword/topic analysis; reverse engineering
- faq-page-generator: PAA questions to FAQ sections; question-based keyword to FAQ content
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Related Skills
google-search-console
41kostja94/marketing-skills
grill-me
386mattpocock/skills
premortem
197parcadei/continuous-claude-v3
deslop
118cursor/plugins
framer-motion
98pproenca/dot-skills
write-a-prd
91mattpocock/skills
Reviews
- SShikha Mishra★★★★★Dec 28, 2024
Registry listing for keyword-research matched our evaluation — installs cleanly and behaves as described in the markdown.
- NNoah White★★★★★Dec 24, 2024
I recommend keyword-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- EEvelyn Patel★★★★★Dec 20, 2024
keyword-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- MMeera Dixit★★★★★Dec 8, 2024
keyword-research reduced setup friction for our internal harness; good balance of opinion and flexibility.
- YYash Thakker★★★★★Nov 19, 2024
Solid pick for teams standardizing on skills: keyword-research is focused, and the summary matches what you get after install.
- BBenjamin Rahman★★★★★Nov 19, 2024
keyword-research reduced setup friction for our internal harness; good balance of opinion and flexibility.
- BBenjamin Ramirez★★★★★Nov 15, 2024
Useful defaults in keyword-research — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- DDhruvi Jain★★★★★Oct 10, 2024
I recommend keyword-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- EEvelyn Rao★★★★★Oct 10, 2024
keyword-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- DDev Nasser★★★★★Oct 6, 2024
Registry listing for keyword-research matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 50
Discussion
Comments — not star reviews- No comments yet — start the thread.