Creator · Affitor
Last updated · Sep 3, 2026
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 cluste
Creator · Affitor
Last updated · Sep 3, 2026
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 cluste
Creator · Affitor
Last updated · Sep 3, 2026
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 cluste
Creator · Affitor
Last updated · Sep 3, 2026
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 cluste
Sandbox only
Install targets
Codex install prompt
Install the "keyword-cluster-architect" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/blog/keyword-cluster-architect. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"affitor-keyword-cluster-architect","task":"Install keyword-cluster-architect","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Maintenance
active
3mo since push
Risk
Needs review
Quality score needs review
GitHub quality
639
73/100 Quality · 80/100 Trust
Coverage tags
Review notes
Quality score needs review · Needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
639 GitHub stars
Repo activity
639 stars, 199 forks
Maintenance
3mo since push
License
MIT
Install
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architectDo not use when
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28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/affitor-keyword-cluster-architect/install
Agent should check
Copy prompt
Task: Use keyword-cluster-architect in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/affitor-keyword-cluster-architect/install
Install command: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/affitor-keyword-cluster-architect/install
LLM text format
/api/skills/affitor-keyword-cluster-architect/install?format=text
Find alternatives
/api/skills/search?q=keyword-cluster-architect&limit=3
Agent prompt
Use keyword-cluster-architect for this task. Review https://www.openagentskill.com/api/skills/affitor-keyword-cluster-architect/install, then install with: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architectRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/affitor-keyword-cluster-architect
LLM text
/api/registry/manifest/affitor-keyword-cluster-architect?format=text
Install alias
/api/registry/install/affitor-keyword-cluster-architect
Recommend
/api/registry/recommend?task=Use%20keyword-cluster-architect%20in%20an%20agent%20workflow&limit=3
Agent fit
Marketing and growth
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Marketing and growth
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO639 GitHub stars
Stars/forks activity
INFO639 stars, 199 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Grow distribution
I need my agent to research keywords, improve SEO, analyze growth channels, and prepare marketing workflows.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Publish consistently
I need my agent to turn research and product updates into useful content drafts.
Workflow fit
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
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--- name: keyword-cluster-architect description: > 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". license: MIT version: "1.0.0" tags: ["affiliate-marketing", "blogging", "seo", "content-writing", "keywords", "clustering"] compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent" metadata: author: affitor version: "1.0" stage: S3-Blog ---
# Keyword Cluster Architect
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.
## Stage
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.
## When to Use
- User wants to plan SEO content strategy for a niche - User asks about keyword research, clustering, or topical authority - User says "keyword", "SEO plan", "content roadmap", "topic cluster", "hub and spoke" - Before running `affiliate-blog-builder` — to know WHICH articles to write - After `monopoly-niche-finder` — to map the keyword universe for the winning niche
## Input Schema
```yaml niche: 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.
## Workflow
### Step 1: Generate Seed Keywords
If not provided, generate 5-10 seed keywords from the niche: - Product-focused: "[product] review", "best [category]" - Problem-focused: "how to [solve problem]", "[problem] solution" - Comparison: "[product A] vs [product B]", "alternatives to [product]" - Tutorial: "how to use [product]", "[product] tutorial"
### Step 2: Expand Keywords
For each seed, use `web_search` to discover related keywords: 1. Search: `"[seed keyword]"` — note related searches, People Also Ask 2. Search: `"[seed keyword] guide" OR "[seed keyword] tutorial"` — informational variants 3. Search: `"best [seed keyword]" OR "[seed keyword] review"` — commercial variants
Collect 50-200+ unique keywords depending on `depth`.
### Step 3: Classify by Intent
Read `shared/references/seo-strategy.md` for clustering methodology.
Classify each keyword: - **Informational** (I): Learning, how-to, what-is → blog posts, tutorials - **Commercial** (C): Comparing, evaluating, reviewing → comparison posts, reviews - **Transactional** (T): Ready to buy, pricing, discount → landing pages, deal pages - **Navigational** (N): Brand-specific, login → skip (not your traffic to capture)
### Step 4: Cluster by Topic
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] ```
### Step 5: Build Content Roadmap
Organize clusters into a hub-and-spoke map:
1. Identify the hub page (broadest, highest-volume cluster) 2. Connect spoke pages (specific clusters that link back to hub) 3. Prioritize by: commercial intent first (revenue), then informational (traffic) 4. Estimate effort: number of articles needed, suggested publishing cadence
### Step 6: Self-Validation
- [ ] Clusters are based on actual search data, not guesses - [ ] Each cluster has a clear search intent (I, C, or T) - [ ] Hub-and-spoke structure is logical (hub is broad, spokes are specific) - [ ] Priority ordering makes business sense (revenue-driving content first) - [ ] Total content pieces are realistic for user's capacity
## Output Schema
```yaml 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" ```
## Output Format
``` ## 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 ```
## Error Handling
- **Niche too broad**: "This niche is very broad. Let me narrow to a sub-niche for more actionable clusters. Or run `monopoly-niche-finder` first." - **No search volume**: "This niche may be too narrow for significant search traffic. Consider broadening slightly." - **Too many keywords**: Group aggressively into fewer clusters. Quality of clustering > quantity of keywords. - **No commercial intent keywords**: Flag as concern — hard to monetize through affiliate without commercial intent. Suggest adjacent niches.
## Examples
**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.
## Flywheel Connections
### Feeds Into - `affiliate-blog-builder` (S3) — which articles to write and target keywords - `comparison-post-writer` (S3) — commercial clusters become comparison articles - `content-moat-calculator` (S3) — keyword count informs moat estimation - `landing-page-creator` (S4) — transactional clusters become landing pages - `internal-linking-optimizer` (S6) — cluster structure defines link architecture
### Fed By - `monopoly-niche-finder` (S1) — niche to cluster keywords for - `content-pillar-atomizer` (S2) — content pillars suggest keyword areas - `seo-audit` (S6) — current ranking data reveals keyword gaps
### Feedback Loop - `seo-audit` (S6) reveals ranking gaps in existing clusters → add keywords and new content to fill gaps
## Quality Gate
Before delivering output, verify:
1. Would I share this on MY personal social? 2. Contains specific, surprising detail? (not generic) 3. Respects reader's intelligence? 4. Remarkable enough to share? (Purple Cow test) 5. Irresistible offer framing? (roadmap feels actionable)
Any NO → rewrite before delivering.
## References
- `shared/references/seo-strategy.md` — Topical authority, clustering methodology, hub-and-spoke - `shared/references/affiliate-glossary.md` — Terminology - `shared/references/flywheel-connections.md` — Master connection map
Source provenance
Decision snapshot
639 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for keyword-cluster-architect, ready for a manual X post.
keyword-cluster-architect: Map 50-200+ keywords into topical clusters for SEO domination. Build content roadmaps for top... 639 stars https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x
Listing + install path for keyword-cluster-architect: https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x Install: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
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Install targets
Codex install prompt
Install the "keyword-cluster-architect" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/blog/keyword-cluster-architect. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"affitor-keyword-cluster-architect","task":"Install keyword-cluster-architect","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Maintenance
active
3mo since push
Risk
Needs review
Quality score needs review
GitHub quality
639
73/100 Quality · 80/100 Trust
Coverage tags
Review notes
Quality score needs review · Needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
639 GitHub stars
Repo activity
639 stars, 199 forks
Maintenance
3mo since push
License
MIT
Install
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architectDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
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28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/affitor-keyword-cluster-architect/install
Agent should check
Copy prompt
Task: Use keyword-cluster-architect in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/affitor-keyword-cluster-architect/install
Install command: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/affitor-keyword-cluster-architect/install
LLM text format
/api/skills/affitor-keyword-cluster-architect/install?format=text
Find alternatives
/api/skills/search?q=keyword-cluster-architect&limit=3
Agent prompt
Use keyword-cluster-architect for this task. Review https://www.openagentskill.com/api/skills/affitor-keyword-cluster-architect/install, then install with: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architectRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/affitor-keyword-cluster-architect
LLM text
/api/registry/manifest/affitor-keyword-cluster-architect?format=text
Install alias
/api/registry/install/affitor-keyword-cluster-architect
Recommend
/api/registry/recommend?task=Use%20keyword-cluster-architect%20in%20an%20agent%20workflow&limit=3
Agent fit
Marketing and growth
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Marketing and growth
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO639 GitHub stars
Stars/forks activity
INFO639 stars, 199 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Grow distribution
I need my agent to research keywords, improve SEO, analyze growth channels, and prepare marketing workflows.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
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--- name: keyword-cluster-architect description: > 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". license: MIT version: "1.0.0" tags: ["affiliate-marketing", "blogging", "seo", "content-writing", "keywords", "clustering"] compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent" metadata: author: affitor version: "1.0" stage: S3-Blog ---
# Keyword Cluster Architect
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.
## Stage
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.
## When to Use
- User wants to plan SEO content strategy for a niche - User asks about keyword research, clustering, or topical authority - User says "keyword", "SEO plan", "content roadmap", "topic cluster", "hub and spoke" - Before running `affiliate-blog-builder` — to know WHICH articles to write - After `monopoly-niche-finder` — to map the keyword universe for the winning niche
## Input Schema
```yaml niche: 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.
## Workflow
### Step 1: Generate Seed Keywords
If not provided, generate 5-10 seed keywords from the niche: - Product-focused: "[product] review", "best [category]" - Problem-focused: "how to [solve problem]", "[problem] solution" - Comparison: "[product A] vs [product B]", "alternatives to [product]" - Tutorial: "how to use [product]", "[product] tutorial"
### Step 2: Expand Keywords
For each seed, use `web_search` to discover related keywords: 1. Search: `"[seed keyword]"` — note related searches, People Also Ask 2. Search: `"[seed keyword] guide" OR "[seed keyword] tutorial"` — informational variants 3. Search: `"best [seed keyword]" OR "[seed keyword] review"` — commercial variants
Collect 50-200+ unique keywords depending on `depth`.
### Step 3: Classify by Intent
Read `shared/references/seo-strategy.md` for clustering methodology.
Classify each keyword: - **Informational** (I): Learning, how-to, what-is → blog posts, tutorials - **Commercial** (C): Comparing, evaluating, reviewing → comparison posts, reviews - **Transactional** (T): Ready to buy, pricing, discount → landing pages, deal pages - **Navigational** (N): Brand-specific, login → skip (not your traffic to capture)
### Step 4: Cluster by Topic
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] ```
### Step 5: Build Content Roadmap
Organize clusters into a hub-and-spoke map:
1. Identify the hub page (broadest, highest-volume cluster) 2. Connect spoke pages (specific clusters that link back to hub) 3. Prioritize by: commercial intent first (revenue), then informational (traffic) 4. Estimate effort: number of articles needed, suggested publishing cadence
### Step 6: Self-Validation
- [ ] Clusters are based on actual search data, not guesses - [ ] Each cluster has a clear search intent (I, C, or T) - [ ] Hub-and-spoke structure is logical (hub is broad, spokes are specific) - [ ] Priority ordering makes business sense (revenue-driving content first) - [ ] Total content pieces are realistic for user's capacity
## Output Schema
```yaml 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" ```
## Output Format
``` ## 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 ```
## Error Handling
- **Niche too broad**: "This niche is very broad. Let me narrow to a sub-niche for more actionable clusters. Or run `monopoly-niche-finder` first." - **No search volume**: "This niche may be too narrow for significant search traffic. Consider broadening slightly." - **Too many keywords**: Group aggressively into fewer clusters. Quality of clustering > quantity of keywords. - **No commercial intent keywords**: Flag as concern — hard to monetize through affiliate without commercial intent. Suggest adjacent niches.
## Examples
**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.
## Flywheel Connections
### Feeds Into - `affiliate-blog-builder` (S3) — which articles to write and target keywords - `comparison-post-writer` (S3) — commercial clusters become comparison articles - `content-moat-calculator` (S3) — keyword count informs moat estimation - `landing-page-creator` (S4) — transactional clusters become landing pages - `internal-linking-optimizer` (S6) — cluster structure defines link architecture
### Fed By - `monopoly-niche-finder` (S1) — niche to cluster keywords for - `content-pillar-atomizer` (S2) — content pillars suggest keyword areas - `seo-audit` (S6) — current ranking data reveals keyword gaps
### Feedback Loop - `seo-audit` (S6) reveals ranking gaps in existing clusters → add keywords and new content to fill gaps
## Quality Gate
Before delivering output, verify:
1. Would I share this on MY personal social? 2. Contains specific, surprising detail? (not generic) 3. Respects reader's intelligence? 4. Remarkable enough to share? (Purple Cow test) 5. Irresistible offer framing? (roadmap feels actionable)
Any NO → rewrite before delivering.
## References
- `shared/references/seo-strategy.md` — Topical authority, clustering methodology, hub-and-spoke - `shared/references/affiliate-glossary.md` — Terminology - `shared/references/flywheel-connections.md` — Master connection map
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keyword-cluster-architect: Map 50-200+ keywords into topical clusters for SEO domination. Build content roadmaps for top... 639 stars https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x
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Academic Research Skills for Claude Code: research → write → review → revise → finalize
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Install the "keyword-cluster-architect" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/blog/keyword-cluster-architect. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"affitor-keyword-cluster-architect","task":"Install keyword-cluster-architect","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
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Task: Use keyword-cluster-architect in this workspace.
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Publish consistently
I need my agent to turn research and product updates into useful content drafts.
Workflow fit
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: keyword-cluster-architect description: > 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". license: MIT version: "1.0.0" tags: ["affiliate-marketing", "blogging", "seo", "content-writing", "keywords", "clustering"] compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent" metadata: author: affitor version: "1.0" stage: S3-Blog ---
# Keyword Cluster Architect
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.
## Stage
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.
## When to Use
- User wants to plan SEO content strategy for a niche - User asks about keyword research, clustering, or topical authority - User says "keyword", "SEO plan", "content roadmap", "topic cluster", "hub and spoke" - Before running `affiliate-blog-builder` — to know WHICH articles to write - After `monopoly-niche-finder` — to map the keyword universe for the winning niche
## Input Schema
```yaml niche: 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.
## Workflow
### Step 1: Generate Seed Keywords
If not provided, generate 5-10 seed keywords from the niche: - Product-focused: "[product] review", "best [category]" - Problem-focused: "how to [solve problem]", "[problem] solution" - Comparison: "[product A] vs [product B]", "alternatives to [product]" - Tutorial: "how to use [product]", "[product] tutorial"
### Step 2: Expand Keywords
For each seed, use `web_search` to discover related keywords: 1. Search: `"[seed keyword]"` — note related searches, People Also Ask 2. Search: `"[seed keyword] guide" OR "[seed keyword] tutorial"` — informational variants 3. Search: `"best [seed keyword]" OR "[seed keyword] review"` — commercial variants
Collect 50-200+ unique keywords depending on `depth`.
### Step 3: Classify by Intent
Read `shared/references/seo-strategy.md` for clustering methodology.
Classify each keyword: - **Informational** (I): Learning, how-to, what-is → blog posts, tutorials - **Commercial** (C): Comparing, evaluating, reviewing → comparison posts, reviews - **Transactional** (T): Ready to buy, pricing, discount → landing pages, deal pages - **Navigational** (N): Brand-specific, login → skip (not your traffic to capture)
### Step 4: Cluster by Topic
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] ```
### Step 5: Build Content Roadmap
Organize clusters into a hub-and-spoke map:
1. Identify the hub page (broadest, highest-volume cluster) 2. Connect spoke pages (specific clusters that link back to hub) 3. Prioritize by: commercial intent first (revenue), then informational (traffic) 4. Estimate effort: number of articles needed, suggested publishing cadence
### Step 6: Self-Validation
- [ ] Clusters are based on actual search data, not guesses - [ ] Each cluster has a clear search intent (I, C, or T) - [ ] Hub-and-spoke structure is logical (hub is broad, spokes are specific) - [ ] Priority ordering makes business sense (revenue-driving content first) - [ ] Total content pieces are realistic for user's capacity
## Output Schema
```yaml 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" ```
## Output Format
``` ## 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 ```
## Error Handling
- **Niche too broad**: "This niche is very broad. Let me narrow to a sub-niche for more actionable clusters. Or run `monopoly-niche-finder` first." - **No search volume**: "This niche may be too narrow for significant search traffic. Consider broadening slightly." - **Too many keywords**: Group aggressively into fewer clusters. Quality of clustering > quantity of keywords. - **No commercial intent keywords**: Flag as concern — hard to monetize through affiliate without commercial intent. Suggest adjacent niches.
## Examples
**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.
## Flywheel Connections
### Feeds Into - `affiliate-blog-builder` (S3) — which articles to write and target keywords - `comparison-post-writer` (S3) — commercial clusters become comparison articles - `content-moat-calculator` (S3) — keyword count informs moat estimation - `landing-page-creator` (S4) — transactional clusters become landing pages - `internal-linking-optimizer` (S6) — cluster structure defines link architecture
### Fed By - `monopoly-niche-finder` (S1) — niche to cluster keywords for - `content-pillar-atomizer` (S2) — content pillars suggest keyword areas - `seo-audit` (S6) — current ranking data reveals keyword gaps
### Feedback Loop - `seo-audit` (S6) reveals ranking gaps in existing clusters → add keywords and new content to fill gaps
## Quality Gate
Before delivering output, verify:
1. Would I share this on MY personal social? 2. Contains specific, surprising detail? (not generic) 3. Respects reader's intelligence? 4. Remarkable enough to share? (Purple Cow test) 5. Irresistible offer framing? (roadmap feels actionable)
Any NO → rewrite before delivering.
## References
- `shared/references/seo-strategy.md` — Topical authority, clustering methodology, hub-and-spoke - `shared/references/affiliate-glossary.md` — Terminology - `shared/references/flywheel-connections.md` — Master connection map
Source provenance
Decision snapshot
639 GitHub stars
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Install and adoption review
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Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for keyword-cluster-architect, ready for a manual X post.
keyword-cluster-architect: Map 50-200+ keywords into topical clusters for SEO domination. Build content roadmaps for top... 639 stars https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x
Listing + install path for keyword-cluster-architect: https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x Install: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
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Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
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Install targets
Codex install prompt
Install the "keyword-cluster-architect" agent skill from https://github.com/Affitor/affiliate-skills/tree/main/skills/blog/keyword-cluster-architect. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"affitor-keyword-cluster-architect","task":"Install keyword-cluster-architect","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
Maintenance
active
3mo since push
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Needs review
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639
73/100 Quality · 80/100 Trust
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Review notes
Quality score needs review · Needs review
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StrongSolid option that is likely worth shortlisting for production workflows.
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Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
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Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
639 GitHub stars
Repo activity
639 stars, 199 forks
Maintenance
3mo since push
License
MIT
Install
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
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Install command
npx skills add Affitor/affiliate-skills --skill keyword-cluster-architectDo not use when
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1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
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npx skills add mvanhorn/last30days-skill -g
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npx skills add Imbad0202/academic-research-skills
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npx skills add assafelovic/gpt-researcher
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Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
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/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
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/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
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/api/skills/affitor-keyword-cluster-architect/install
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Task: Use keyword-cluster-architect in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20keyword-cluster-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/affitor-keyword-cluster-architect/install
Install command: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
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/api/skills/search?q=keyword-cluster-architect&limit=3
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Use keyword-cluster-architect for this task. Review https://www.openagentskill.com/api/skills/affitor-keyword-cluster-architect/install, then install with: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architectRegistry metadata
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/api/registry/install/affitor-keyword-cluster-architect
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/api/registry/recommend?task=Use%20keyword-cluster-architect%20in%20an%20agent%20workflow&limit=3
Agent fit
Marketing and growth
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
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Primary pick
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Marketing and growth
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Use when
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review first
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Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO639 GitHub stars
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INFO639 stars, 199 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Grow distribution
I need my agent to research keywords, improve SEO, analyze growth channels, and prepare marketing workflows.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Publish consistently
I need my agent to turn research and product updates into useful content drafts.
Workflow fit
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: keyword-cluster-architect description: > 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". license: MIT version: "1.0.0" tags: ["affiliate-marketing", "blogging", "seo", "content-writing", "keywords", "clustering"] compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent" metadata: author: affitor version: "1.0" stage: S3-Blog ---
# Keyword Cluster Architect
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.
## Stage
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.
## When to Use
- User wants to plan SEO content strategy for a niche - User asks about keyword research, clustering, or topical authority - User says "keyword", "SEO plan", "content roadmap", "topic cluster", "hub and spoke" - Before running `affiliate-blog-builder` — to know WHICH articles to write - After `monopoly-niche-finder` — to map the keyword universe for the winning niche
## Input Schema
```yaml niche: 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.
## Workflow
### Step 1: Generate Seed Keywords
If not provided, generate 5-10 seed keywords from the niche: - Product-focused: "[product] review", "best [category]" - Problem-focused: "how to [solve problem]", "[problem] solution" - Comparison: "[product A] vs [product B]", "alternatives to [product]" - Tutorial: "how to use [product]", "[product] tutorial"
### Step 2: Expand Keywords
For each seed, use `web_search` to discover related keywords: 1. Search: `"[seed keyword]"` — note related searches, People Also Ask 2. Search: `"[seed keyword] guide" OR "[seed keyword] tutorial"` — informational variants 3. Search: `"best [seed keyword]" OR "[seed keyword] review"` — commercial variants
Collect 50-200+ unique keywords depending on `depth`.
### Step 3: Classify by Intent
Read `shared/references/seo-strategy.md` for clustering methodology.
Classify each keyword: - **Informational** (I): Learning, how-to, what-is → blog posts, tutorials - **Commercial** (C): Comparing, evaluating, reviewing → comparison posts, reviews - **Transactional** (T): Ready to buy, pricing, discount → landing pages, deal pages - **Navigational** (N): Brand-specific, login → skip (not your traffic to capture)
### Step 4: Cluster by Topic
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] ```
### Step 5: Build Content Roadmap
Organize clusters into a hub-and-spoke map:
1. Identify the hub page (broadest, highest-volume cluster) 2. Connect spoke pages (specific clusters that link back to hub) 3. Prioritize by: commercial intent first (revenue), then informational (traffic) 4. Estimate effort: number of articles needed, suggested publishing cadence
### Step 6: Self-Validation
- [ ] Clusters are based on actual search data, not guesses - [ ] Each cluster has a clear search intent (I, C, or T) - [ ] Hub-and-spoke structure is logical (hub is broad, spokes are specific) - [ ] Priority ordering makes business sense (revenue-driving content first) - [ ] Total content pieces are realistic for user's capacity
## Output Schema
```yaml 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" ```
## Output Format
``` ## 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 ```
## Error Handling
- **Niche too broad**: "This niche is very broad. Let me narrow to a sub-niche for more actionable clusters. Or run `monopoly-niche-finder` first." - **No search volume**: "This niche may be too narrow for significant search traffic. Consider broadening slightly." - **Too many keywords**: Group aggressively into fewer clusters. Quality of clustering > quantity of keywords. - **No commercial intent keywords**: Flag as concern — hard to monetize through affiliate without commercial intent. Suggest adjacent niches.
## Examples
**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.
## Flywheel Connections
### Feeds Into - `affiliate-blog-builder` (S3) — which articles to write and target keywords - `comparison-post-writer` (S3) — commercial clusters become comparison articles - `content-moat-calculator` (S3) — keyword count informs moat estimation - `landing-page-creator` (S4) — transactional clusters become landing pages - `internal-linking-optimizer` (S6) — cluster structure defines link architecture
### Fed By - `monopoly-niche-finder` (S1) — niche to cluster keywords for - `content-pillar-atomizer` (S2) — content pillars suggest keyword areas - `seo-audit` (S6) — current ranking data reveals keyword gaps
### Feedback Loop - `seo-audit` (S6) reveals ranking gaps in existing clusters → add keywords and new content to fill gaps
## Quality Gate
Before delivering output, verify:
1. Would I share this on MY personal social? 2. Contains specific, surprising detail? (not generic) 3. Respects reader's intelligence? 4. Remarkable enough to share? (Purple Cow test) 5. Irresistible offer framing? (roadmap feels actionable)
Any NO → rewrite before delivering.
## References
- `shared/references/seo-strategy.md` — Topical authority, clustering methodology, hub-and-spoke - `shared/references/affiliate-glossary.md` — Terminology - `shared/references/flywheel-connections.md` — Master connection map
Source provenance
Decision snapshot
639 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for keyword-cluster-architect, ready for a manual X post.
keyword-cluster-architect: Map 50-200+ keywords into topical clusters for SEO domination. Build content roadmaps for top... 639 stars https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x
Listing + install path for keyword-cluster-architect: https://www.openagentskill.com/skills/affitor-keyword-cluster-architect?ref=x Install: npx skills add Affitor/affiliate-skills --skill keyword-cluster-architect
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsPermission surface
shell or command execution, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, database access
Agent outcomes
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Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness