
Keyword Research
- 990 installs
- 787 repo stars
- Updated June 9, 2026
- kostja94/marketing-skills
keyword-research is an agent skill (v1.3.1) that guides developers through SEO keyword discovery, intent classification, clustering, and topical-map planning to prioritize high-intent organic search terms.
About
keyword-research is a Marketing & SEO agent skill (v1.3.1) from kostja94/marketing-skills that walks developers through finding target keywords, scoring difficulty, classifying search intent, and building pillar–cluster topical maps. The workflow covers five base discovery methods—user perspective, tool expansion, competitor reverse engineering, Google People Also Ask, and article extraction—plus Google autocomplete long-tail expansion using the alphabet method across 26 letters and digits 0–9. keyword-research notes that roughly 95% of keywords get fewer than 10 searches per month and about 70% of search traffic is long-tail, so the screening workflow filters volume, KD, CPC, and SERP features before mapping keywords to pages. Reach for keyword-research when planning blog posts, docs, or product landing pages and you need a prioritized keyword list, content-gap report, and topical map instead of guessing titles.
- Analyzes search intent and keyword difficulty using real discovery methods
- Builds topical maps and keyword clusters for content strategy
- Incorporates Google autocomplete, People Also Ask, and alphabet method
- Reads project-context.md to tailor recommendations to your product and audience
- Highlights that ~95% of keywords receive fewer than 10 searches per month
Keyword Research by the numbers
- 990 all-time installs (skills.sh)
- +6 installs in the week ending Jul 29, 2026 (Skillselion tracking)
- Ranked #439 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Jul 31, 2026 (Skillselion catalog sync)
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| Installs | 990 |
|---|---|
| repo stars | ★ 787 |
| Security audit | 2 / 3 scanners passed |
| Last updated | June 9, 2026 |
| Repository | kostja94/marketing-skills ↗ |
How do you find low-competition SEO keywords?
Discover high-intent, low-competition keywords and build topical maps that drive organic traffic.
Who is it for?
Developers shipping documentation, blogs, or marketing sites who need data-backed keyword targets before writing pages or briefs.
Skip if: Teams that only need on-page copy edits, paid-search-only campaigns without organic research, or full content-calendar execution—use content-strategy instead.
When should I use this skill?
User mentions keyword research, search volume, search intent, keyword difficulty, topical map, Google autocomplete, People Also Ask, or alphabet-method discovery.
What you get
Prioritized keyword spreadsheet, intent-labeled clusters, pillar–cluster topical map, content-gap list, and page-to-keyword mapping report.
- Prioritized keyword list with volume KD and intent
- Pillar–cluster topical map
- Content-gap and keyword-mapping report
By the numbers
- Skill version 1.3.1 in marketing-skills SEO content track
- Documents ~95% of keywords get fewer than 10 searches per month
- Notes ~70% of search traffic is long-tail with lower competition
Files
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: 1. Product/service: What you offer 2. Audience: Who searches for it 3. Goals: Traffic, conversions, brand 4. 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
1. Parse — Read Excel/CSV, infer keyword, volume, KD, intent, etc. from headers 2. Enrich — Web search, visit competitor/product pages; read project-context.md if present 3. Build — Structure data for report 4. 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
Related skills
How it compares
Pick keyword-research when you need discovery, intent labeling, and topical-map structure; switch to content-strategy once clusters are defined and you need editorial planning and page production workflows.
FAQ
What does the keyword-research skill output?
keyword-research outputs a prioritized keyword list with volume, KD, and intent labels, a pillar–cluster topical map, page-to-keyword mapping, a competitor content-gap list, and an action plan with top priorities. Reports can be generated from CSV or Excel inputs.
How does keyword-research find long-tail keywords?
keyword-research uses Google autocomplete with the alphabet method—typing a seed plus each letter a–z and digits 0–9—to surface real queries tools often filter out. The skill pairs autocomplete with People Also Ask, Related Searches, and intent modifiers like how, best, and vs.
When should developers use keyword-research vs content-strategy?
keyword-research handles discovery, intent scoring, clustering, and topical-map planning. content-strategy takes finalized clusters into editorial calendars, pillar pages, and production workflows. Run keyword-research first when you lack a validated target keyword list.
Is Keyword Research safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.