Agent skill
programmatic-seo
Plan and blueprint programmatic SEO page strategies at scale
Filed under Content and SEO.
From ekatasingh1107/b2b-gtm-skills · 99 skills · 2 · pushed 2026-04-11
What it does when it runs
Plan and blueprint programmatic SEO page strategies at scale
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Install it
View source on GitHub ↗git clone --depth 1 --filter=blob:none --sparse https://github.com/ekatasingh1107/b2b-gtm-skills.git /tmp/b2b-gtm-skills git -C /tmp/b2b-gtm-skills sparse-checkout set "skills/composites/programmatic-seo" mkdir -p ~/.claude/skills/programmatic-seo cp -R "/tmp/b2b-gtm-skills/skills/composites/programmatic-seo/." ~/.claude/skills/programmatic-seo/
Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗
The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.
The skill
Source on GitHub ↗Reproduced in full from ekatasingh1107/b2b-gtm-skills/blob/eae8dd0bb98da1c8e84abd297066a87015dd860f/skills/composites/programmatic-seo/SKILL.md, which is licensed MIT (repository). 1,630 words, 27 headings.
Programmatic SEO
Plans programmatic SEO strategies by identifying repeatable page patterns (service + location, service + industry, tool + use case), defining template structures, identifying data sources for dynamic content, planning internal linking strategies, and estimating page count and traffic potential. Outputs a complete programmatic SEO blueprint ready for implementation.
Prerequisites
- WebSearch tool available for SERP analysis and pattern validation
- Browser automation tool for analyzing competitor programmatic pages
- Business services, target locations, or target verticals to combine
- Optional:
agency.config.jsonfor service and ICP context
Capabilities Used
keyword-miner-- for validating search volume of programmatic keyword patternscontent-seo-optimizer-- for optimizing page templatesschema-generator-- for generating template-level structured data
Phase 0: Read Config
- Read
agency.config.jsonfrom the project root (if available). - Extract
services[]for service-based page patterns. - Extract
icp.segments[].industriesfor industry-based page patterns. - Extract
icp.segments[].geosfor location-based page patterns. - Accept parameters:
domain-- (required) target website domainpattern_type-- (optional)service_location|service_industry|tool_usecase|comparison|integration|template_gallery|auto. Default:auto(analyze and recommend)services-- (optional) array of services to create pages forlocations-- (optional) array of locations for location pagesindustries-- (optional) array of industries for vertical pagesmax_pages-- (optional) maximum page count to plan. Default: 500
Phase 1: Pattern Identification
Analyze Existing Site Structure
- Visit the domain via browser automation
- Map current page types and URL patterns
- Identify existing programmatic pages (if any)
- Note the site's CMS and templating capabilities
- Count current indexed pages: WebSearch
site:{{domain}}
Identify Repeatable Patterns
Based on the business type, evaluate these programmatic patterns:
Service + Location (most common for agencies and service businesses)
- Pattern:
/{{service}}/{{city}}or/{{service}}-in-{{city}} - Example:
/shopify-development/mumbai,/shopify-development/delhi - Works when: business serves multiple geographic markets
Service + Industry
- Pattern:
/{{service}}/{{industry}}or/{{service}}-for-{{industry}} - Example:
/shopify-development/fashion-brands,/cro-audit/electronics - Works when: service delivery varies by vertical
Tool/Feature + Use Case
- Pattern:
/tools/{{tool}}/{{use-case}}or/features/{{feature}}-for-{{goal}} - Example:
/tools/ab-testing/product-pages,/features/checkout-optimization-for-aov - Works when: product has multiple features or use cases
Comparison Pages
- Pattern:
/compare/{{your-product}}-vs-{{competitor}} - Example:
/compare/plasho-vs-competitor-agency - Works when: prospects are comparing solutions
Integration Pages
- Pattern:
/integrations/{{platform}}or/works-with/{{tool}} - Example:
/integrations/klaviyo,/works-with/google-analytics - Works when: product/service integrates with other tools
Template/Example Gallery
- Pattern:
/templates/{{category}}/{{subcategory}} - Example:
/templates/fashion/minimalist,/examples/food-beverage/premium - Works when: showcasing portfolio or template variety
Competitor Programmatic Page Analysis
- WebSearch:
site:{{competitor}} inurl:{{pattern_slug}}-- find competitor programmatic pages - Analyze competitor page templates, content patterns, internal linking
- Note what ranks well and what doesn't
- Identify patterns competitors use that the target does not
Phase 2: Keyword Validation
Generate Keyword Matrix
For the chosen pattern, generate the full keyword matrix:
- List all dimension A values (services, tools, features)
- List all dimension B values (locations, industries, use cases)
- Create the cross-product: A x B = total page list
Validate Search Demand
For a sample of 20-30 keyword combinations:
- WebSearch each combination to check for:
- Search results count (more results = more demand)
- Autocomplete suggestions (confirms search volume)
- "People Also Ask" presence (confirms informational demand)
- Competitor pages ranking (confirms commercial viability)
- Categorize demand levels: High, Medium, Low, No demand
Filter and Prioritize
- Remove combinations with no search demand
- Rank remaining by estimated volume and commercial intent
- Identify "head" terms (high volume, competitive) vs "long tail" (low volume, easy)
- Calculate total addressable search volume for the page set
Phase 3: Template Structure Design
Page Template Components
Define the standard template structure for the programmatic pages:
Above the Fold
- Dynamic H1:
{{Service}} in {{Location}}or{{Service}} for {{Industry}} - Dynamic meta title:
{{Service}} {{Modifier}} in {{Location}} | {{Brand}} - Dynamic meta description template
- Hero section with dynamic city/industry imagery or relevant visual
- Primary CTA (contact, demo, quote)
Body Content Sections
- Introduction paragraph (template with dynamic variables)
- Service/product details specific to the dimension (location-specific info, industry-specific pain points)
- Benefits section (can be partially templated, partially dynamic)
- Social proof: case studies, testimonials, reviews filtered by dimension
- FAQ section: dimension-specific FAQ pairs
- Related services/pages: internal links to sibling pages
Below the Fold
- Trust signals (logos, certifications, awards)
- Secondary CTA
- Related content links
Content Differentiation Strategy
The biggest risk in programmatic SEO is thin/duplicate content. Plan for:
- Unique intro paragraph per page (at least 2-3 sentences unique to each dimension)
- Dimension-specific data (location stats, industry benchmarks, relevant case studies)
- Dynamic FAQ pairs (different questions per dimension)
- Unique internal links (each page links to different related pages)
- Minimum unique content per page: 300+ words beyond shared template content
Phase 4: Data Source Planning
Identify Data Sources for Dynamic Content
For each dynamic element, specify where the data comes from:
| Dynamic Element | Data Source | Update Frequency |
|---|---|---|
| Location stats | Census data, Wikipedia, public APIs | Yearly |
| Industry benchmarks | Industry reports, public studies | Quarterly |
| Case studies | Internal CMS / portfolio database | As created |
| Testimonials | Review platforms, CRM | Monthly |
| FAQ pairs | Customer support data, PAA mining | Quarterly |
| Local imagery | Stock photo APIs, local photography | Once |
| Pricing variations | Internal pricing database | As changed |
Data Collection Plan
- List all data points needed per dimension
- Identify free vs paid data sources
- Estimate data collection effort per dimension
- Plan for data freshness: how often does each data point need updating?
Phase 5: Internal Linking Architecture
Hub and Spoke Model
- Hub page: main service/category page that links to all programmatic child pages
- Spoke pages: individual programmatic pages that link back to hub + to 3-5 sibling pages
- Cross-links: programmatic pages in one dimension link to related pages in another dimension
Link Structure
/services/shopify-development (hub)
-> /shopify-development/mumbai (spoke)
-> /shopify-development/delhi (spoke)
-> /shopify-development/bangalore (spoke)
Each spoke links to:
- Hub page (parent)
- 3-5 sibling spokes (nearest cities or most relevant)
- Related service pages (cross-dimension)
- Blog posts about the dimension topic
Sitemap Strategy
- Generate XML sitemap for all programmatic pages
- Group by dimension in sitemap index
- Set appropriate change frequency and priority
- Plan for sitemap updates as new pages are added
Phase 6: Implementation Roadmap
Phase-Based Rollout
Recommend staged deployment:
- Pilot (Week 1-2): Build 10-20 pages for highest-demand combinations. Monitor indexing, rankings, and traffic.
- Validation (Week 3-4): Analyze pilot performance. Refine template based on what ranks. Fix any indexing issues.
- Scale (Week 5-8): Expand to next 50-100 pages. Add unique content and data enrichment.
- Full deployment (Month 3+): Launch remaining pages. Ongoing content quality improvements.
Technical Requirements
- CMS template capability or static site generation
- Dynamic content rendering (server-side preferred for SEO)
- URL management and canonical tag strategy
- Internal linking automation
- Sitemap generation and submission
Phase 7: Output
Return structured JSON:
{
"domain": "example.com",
"planned_at": "2024-01-15T14:30:00Z",
"pattern_type": "service_location",
"total_pages_planned": 150,
"dimensions": {
"dimension_a": {
"name": "Services",
"values": ["shopify-development", "cro-audit", "store-migration"],
"count": 3
},
"dimension_b": {
"name": "Locations",
"values": ["mumbai", "delhi", "bangalore", "hyderabad", "pune"],
"count": 50
}
},
"keyword_validation": {
"total_combinations": 150,
"validated_sample_size": 25,
"demand_distribution": {
"high": 8,
"medium": 10,
"low": 5,
"no_demand": 2
},
"estimated_total_monthly_volume": "5K-15K",
"top_keywords": [
{ "keyword": "shopify development mumbai", "estimated_volume": "Medium", "difficulty": "Easy" }
]
},
"template_structure": {
"url_pattern": "/{{service}}/{{location}}",
"title_template": "{{Service}} in {{Location}} | Expert Shopify Agency | {{Brand}}",
"meta_description_template": "Looking for {{service}} in {{location}}? We help {{location}} brands...",
"sections": [
"Dynamic H1 + hero",
"Location-specific intro (unique 150+ words)",
"Service details",
"Local case studies / testimonials",
"Location stats and market data",
"FAQ (5 location-specific questions)",
"CTA + contact info",
"Related service pages"
],
"min_unique_content_per_page": "300 words"
},
"data_sources": [
{ "element": "Location population and market data", "source": "Census / Wikipedia", "collection_effort": "Low (automated)" },
{ "element": "Industry-specific pain points", "source": "Customer interviews + ICP research", "collection_effort": "Medium (manual)" }
],
"internal_linking_plan": {
"hub_pages": ["/services/shopify-development"],
"sibling_links_per_page": 5,
"cross_dimension_links": 2,
"blog_content_links": 1
},
"rollout_plan": {
"pilot": { "pages": 15, "timeline": "Week 1-2", "focus": "Top 5 cities x 3 services" },
"validation": { "timeline": "Week 3-4", "metrics": ["Indexing rate", "Ranking positions", "Organic clicks"] },
"scale": { "pages": 50, "timeline": "Week 5-8" },
"full_deployment": { "pages": 150, "timeline": "Month 3+" }
},
"traffic_projection": {
"month_3": "500-1000 organic visits/month",
"month_6": "2000-5000 organic visits/month",
"month_12": "5000-15000 organic visits/month"
},
"risks_and_mitigations": [
{ "risk": "Thin content penalty", "mitigation": "Minimum 300 unique words per page, noindex low-quality pages until content is added" },
{ "risk": "Crawl budget waste", "mitigation": "Prioritize high-demand pages in sitemap, use internal linking to signal importance" },
{ "risk": "Cannibalization with existing pages", "mitigation": "Clear canonical strategy, distinct keyword targeting per page" }
]
}
Example Usage
Trigger phrases:
- "Plan programmatic SEO for [domain]"
- "Create location pages strategy for [business]"
- "Programmatic SEO blueprint for [service] + [dimension]"
- "How many pages should I create for [niche]?"
- "Scale content with programmatic SEO"
User: Plan programmatic SEO for plasho.com -- service + city pages for India
Assistant: [identifies services from config, generates city list, validates keyword demand, designs template, plans rollout, returns complete blueprint]
User: Programmatic SEO strategy: shopify development + industry verticals
Assistant: [maps services to industries, validates search demand per combo, designs template with industry-specific content, returns implementation plan]
User: Should I create comparison pages for plasho.com?
Assistant: [researches "plasho vs" queries, analyzes competitor comparison pages, evaluates demand, recommends if viable, returns blueprint if yes]
Files bundled with it
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Need help setting it up?
This page tells you what programmatic-seo does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.
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