skills/blog/keyword-cluster-architect/SKILL.md
Map 50-200+ keywords into topical clusters for SEO domination. Build content roadmaps for topical authority. Triggers on: "keyword research", "keyword clustering", "topical authority", "keyword map", "keyword strategy", "content roadmap for SEO", "keyword grouping", "topic clusters", "SEO keyword plan", "map my keywords", "keyword cluster", "hub and spoke content", "build topical authority", "SEO content plan", "keyword universe".
npx skillsauth add affitor/affiliate-skills keyword-cluster-architectInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Map 50-200+ keywords into topical clusters grouped by search intent. Build a content roadmap for dominating a topic with hub-and-spoke architecture. Google rewards topical authority — this skill builds the strategic map that tells you exactly what content to create and in what order.
S3: Blog & SEO — This is the strategic planning layer FOR blog content. Before writing individual posts, you need a map of the entire keyword landscape organized into clusters.
affiliate-blog-builder — to know WHICH articles to writemonopoly-niche-finder — to map the keyword universe for the winning nicheniche: string # REQUIRED — the topic to cluster
# e.g., "AI video tools", "email marketing for SaaS"
seed_keywords: string[] # OPTIONAL — starting keywords to expand from
# Default: auto-generated from niche
depth: string # OPTIONAL — "quick" (50 keywords) | "standard" (100) | "deep" (200+)
# Default: "standard"
affiliate_products: string[] # OPTIONAL — products you promote (to prioritize commercial keywords)
# Default: none
Chaining from S1 monopoly-niche-finder: Use monopoly_niche.intersection as the niche input.
If not provided, generate 5-10 seed keywords from the niche:
For each seed, use web_search to discover related keywords:
"[seed keyword]" — note related searches, People Also Ask"[seed keyword] guide" OR "[seed keyword] tutorial" — informational variants"best [seed keyword]" OR "[seed keyword] review" — commercial variantsCollect 50-200+ unique keywords depending on depth.
Read shared/references/seo-strategy.md for clustering methodology.
Classify each keyword:
Group keywords that share the same search intent (would be answered by the same page):
Cluster: "[Main Topic]"
Type: [I/C/T]
Hub keyword: [highest volume keyword]
Supporting keywords:
- [keyword 1] — [est. volume]
- [keyword 2] — [est. volume]
Content type: [blog post / comparison / review / tutorial / landing page]
Priority: [1-5 based on volume × intent × competition]
Organize clusters into a hub-and-spoke map:
output_schema_version: "1.0.0"
keyword_clusters:
niche: string
total_keywords: number
total_clusters: number
hub:
keyword: string
cluster_name: string
content_type: string
priority: number
clusters:
- name: string
intent: string # "informational" | "commercial" | "transactional"
hub_keyword: string
keywords: string[]
content_type: string # "blog" | "comparison" | "review" | "tutorial" | "landing"
priority: number # 1-5
estimated_volume: string
content_roadmap:
total_articles: number
publishing_cadence: string
priority_order: string[] # Cluster names in order to write
target_keywords: string[] # Flat list of all keywords for chaining
chain_metadata:
skill_slug: "keyword-cluster-architect"
stage: "blog"
timestamp: string
suggested_next:
- "affiliate-blog-builder"
- "content-moat-calculator"
- "comparison-post-writer"
- "landing-page-creator"
## Keyword Cluster Map: [Niche]
### Overview
- **Total keywords:** XXX
- **Clusters:** XX
- **Hub topic:** [main hub]
- **Content pieces needed:** XX articles
### Hub & Spoke Map
[HUB: Main Topic]
/ | | \
[Spoke] [Spoke] [Spoke] [Spoke]
| | | |
[Sub] [Sub] [Sub] [Sub]
### Clusters by Priority
#### Priority 1: [Cluster Name] (Commercial Intent)
- **Hub keyword:** [keyword] — [volume]
- **Content type:** [comparison / review]
- **Keywords:** [list]
- **Article idea:** [specific title]
#### Priority 2: [Cluster Name] (Informational Intent)
[same structure]
[Continue for all clusters]
### Content Roadmap
| Week | Cluster | Article | Intent | Priority |
|---|---|---|---|---|
| 1 | [cluster] | [title] | C | 1 |
| 2 | [cluster] | [title] | C | 1 |
| 3 | [cluster] | [title] | I | 2 |
### Next Steps
- Run `content-moat-calculator` to estimate effort for topical authority
- Run `affiliate-blog-builder` for Priority 1 articles
- Run `comparison-post-writer` for commercial clusters
monopoly-niche-finder first."Example 1: "Map keywords for AI video tools" → Seeds: "best AI video tools", "AI video generator", "HeyGen review". Expand to 100+ keywords. Cluster: "AI video reviews" (C), "how to make AI videos" (I), "AI video pricing" (T), "AI video vs traditional" (C). Hub: "Best AI Video Tools 2025".
Example 2: "Keyword strategy for my affiliate blog about email marketing" → Deep keyword research. Clusters: "email marketing platforms" (C), "email automation tutorials" (I), "email marketing pricing comparison" (T), "email deliverability guides" (I).
Example 3: "Plan my content roadmap" (after monopoly-niche-finder) → Pick up niche from chain. Map 100+ keywords in that intersection niche. Prioritize clusters by revenue potential.
affiliate-blog-builder (S3) — which articles to write and target keywordscomparison-post-writer (S3) — commercial clusters become comparison articlescontent-moat-calculator (S3) — keyword count informs moat estimationlanding-page-creator (S4) — transactional clusters become landing pagesinternal-linking-optimizer (S6) — cluster structure defines link architecturemonopoly-niche-finder (S1) — niche to cluster keywords forcontent-pillar-atomizer (S2) — content pillars suggest keyword areasseo-audit (S6) — current ranking data reveals keyword gapsseo-audit (S6) reveals ranking gaps in existing clusters → add keywords and new content to fill gapsBefore delivering output, verify:
Any NO → rewrite before delivering.
shared/references/seo-strategy.md — Topical authority, clustering methodology, hub-and-spokeshared/references/affiliate-glossary.md — Terminologyshared/references/flywheel-connections.md — Master connection mapdevelopment
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