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coreyhaines31/programmatic-seo

coreyhaines31

programmatic-seo

When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," "building many pages for SEO," "pSEO," "generate 100 pages," "data-driven pages," or "templated landing pages." Use this whenever someone wants to create many similar pages targeting different keywords or locations. For auditing existing SEO issues, see seo-audit. For content strategy planning, see content-strategy.

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v1.2Saved Jun 28, 2026

Programmatic SEO

You are an expert in programmatic SEO—building SEO-optimized pages at scale using templates and data. Your goal is to create pages that rank, provide value, and avoid thin content penalties.

Initial Assessment

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Before designing a programmatic SEO strategy, understand:

  1. Business Context

    • What's the product/service?
    • Who is the target audience?
    • What's the conversion goal for these pages?
  2. Opportunity Assessment

    • What search patterns exist?
    • How many potential pages?
    • What's the search volume distribution?
  3. Competitive Landscape

    • Who ranks for these terms now?
    • What do their pages look like?
    • Can you realistically compete?

Core Principles

1. Unique Value Per Page

  • Every page must provide value specific to that page
  • Not just swapped variables in a template
  • Maximize unique content—the more differentiated, the better

2. Proprietary Data Wins

Hierarchy of data defensibility:

  1. Proprietary (you created it)
  2. Product-derived (from your users)
  3. User-generated (your community)
  4. Licensed (exclusive access)
  5. Public (anyone can use—weakest)

3. Clean URL Structure

Use subfolders, not subdomains — subfolders consolidate domain authority while subdomains split it:

  • Good: yoursite.com/templates/resume/
  • Bad: templates.yoursite.com/resume/

4. Genuine Search Intent Match

Pages must actually answer what people are searching for.

5. Quality Over Quantity

Better to have 100 great pages than 10,000 thin ones.

6. Avoid Google Penalties

  • No doorway pages
  • No keyword stuffing
  • No duplicate content
  • Genuine utility for users

The 12 Playbooks (Overview)

Playbook Pattern Example
Templates "[Type] template" "resume template"
Curation "best [category]" "best website builders"
Conversions "[X] to [Y]" "$10 USD to GBP"
Comparisons "[X] vs [Y]" "webflow vs wordpress"
Examples "[type] examples" "landing page examples"
Locations "[service] in [location]" "dentists in austin"
Personas "[product] for [audience]" "crm for real estate"
Integrations "[product A] [product B] integration" "slack asana integration"
Glossary "what is [term]" "what is pSEO"
Translations Content in multiple languages Localized content
Directory "[category] tools" "ai copywriting tools"
Profiles "[entity name]" "stripe ceo"

For detailed playbook implementation: See references/playbooks.md


Choosing Your Playbook

If you have... Consider...
Proprietary data Directories, Profiles
Product with integrations Integrations
Design/creative product Templates, Examples
Multi-segment audience Personas
Local presence Locations
Tool or utility product Conversions
Content/expertise Glossary, Curation
Competitor landscape Comparisons

You can layer multiple playbooks (e.g., "Best coworking spaces in San Diego").


Implementation Framework

1. Keyword Pattern Research

Identify the pattern:

  • What's the repeating structure?
  • What are the variables?
  • How many unique combinations exist?

Validate demand:

  • Aggregate search volume
  • Volume distribution (head vs. long tail)
  • Trend direction

2. Data Requirements

Identify data sources:

  • What data populates each page?
  • Is it first-party, scraped, licensed, public?
  • How is it updated?

3. Template Design

Page structure:

  • Header with target keyword
  • Unique intro (not just variables swapped)
  • Data-driven sections
  • Related pages / internal links
  • CTAs appropriate to intent

Ensuring uniqueness:

  • Each page needs unique value
  • Conditional content based on data
  • Original insights/analysis per page

4. Internal Linking Architecture

Hub and spoke model:

  • Hub: Main category page
  • Spokes: Individual programmatic pages
  • Cross-links between related spokes

Avoid orphan pages:

  • Every page reachable from main site
  • XML sitemap for all pages
  • Breadcrumbs with structured data

5. Indexation Strategy

  • Prioritize high-volume patterns
  • Noindex very thin variations
  • Manage crawl budget thoughtfully
  • Separate sitemaps by page type

Quality Checks

Pre-Launch Checklist

Content quality:

  • Each page provides unique value
  • Answers search intent
  • Readable and useful

Technical SEO:

  • Unique titles and meta descriptions
  • Proper heading structure
  • Schema markup implemented
  • Page speed acceptable

Internal linking:

  • Connected to site architecture
  • Related pages linked
  • No orphan pages

Indexation:

  • In XML sitemap
  • Crawlable
  • No conflicting noindex

Post-Launch Monitoring

Track: Indexation rate, Rankings, Traffic, Engagement, Conversion

Watch for: Thin content warnings, Ranking drops, Manual actions, Crawl errors


Common Mistakes

  • Thin content: Just swapping city names in identical content
  • Keyword cannibalization: Multiple pages targeting same keyword
  • Over-generation: Creating pages with no search demand
  • Poor data quality: Outdated or incorrect information
  • Ignoring UX: Pages exist for Google, not users

Output Format

Strategy Document

  • Opportunity analysis
  • Implementation plan
  • Content guidelines

Page Template

  • URL structure
  • Title/meta templates
  • Content outline
  • Schema markup

Task-Specific Questions

  1. What keyword patterns are you targeting?
  2. What data do you have (or can acquire)?
  3. How many pages are you planning?
  4. What does your site authority look like?
  5. Who currently ranks for these terms?
  6. What's your technical stack?

  • seo-audit: For auditing programmatic pages after launch
  • schema: For adding structured data
  • site-architecture: For page hierarchy, URL structure, and internal linking
  • competitors: For comparison page frameworks
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Overall Score

82/100

Grade

B

Good

Safety

90

Quality

82

Clarity

85

Completeness

72

Summary

This skill teaches AI agents to design and execute programmatic SEO strategies—building SEO-optimized pages at scale using templates and data. It provides a structured framework covering 12 playbooks (Templates, Curation, Comparisons, etc.), core principles, implementation guidance, quality checks, and decision trees for choosing the right approach based on available assets.

Detected Capabilities

Read product-marketing context filesAnalyze keyword patterns and demand validationDesign page templates and URL structuresGenerate content outlines with unique value per pageRecommend schema markup and structured dataAssess competitive landscape and ranking feasibilityDefine internal linking strategies at scaleMonitor and audit indexation health

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

programmatic seo strategytemplate pages at scalelocation pagescomparison pagesintegration pagescreate many pagespseodata-driven pagestemplate-based landing pages

Use Cases

  • Creating 100+ CRM pages targeting different industries or company sizes
  • Building comparison pages for all competitor alternatives at scale
  • Launching integration pages for 50+ connected tools
  • Generating location-specific service pages across multiple cities
  • Publishing glossary definitions to rank for informational keywords
  • Creating persona-specific landing pages (e.g., 'Notion for designers' vs 'Notion for project managers')
  • Building template galleries to capture high-intent search traffic
  • Scaling directory or curation pages with unique evaluation criteria

Quality Notes

  • Skill is pedagogical rather than operational—teaches strategy and frameworks rather than executing file changes or code generation, which is appropriate for programmatic SEO planning
  • Comprehensive coverage of 12 distinct playbooks with pattern examples and applicability matrix—very well-structured reference
  • Strong emphasis on avoiding thin content and Google penalties, with explicit warnings about keyword stuffing and duplicate content
  • Includes concrete decision trees and checklists (Initial Assessment, Quality Checks pre-launch, post-launch monitoring)
  • Evaluation suite (evals.json) covers both happy-path scenarios and troubleshooting (indexation problems, audit task delegation)
  • Clear scope boundaries: skill handles strategy and planning; defers to seo-audit for technical issues, competitors for comparison frameworks, schema for structured data
  • References external playbooks.md file with detailed implementation for each of 12 patterns—good modularization
  • Task-specific questions at the end help agents gather required context before designing strategy
  • Contextual enhancement: checks for product-marketing.md before asking questions, avoiding duplicate information gathering
  • All supporting files are present and referenced correctly (playbooks.md, evals.json, LICENSE)
  • Minor ambiguity: 'Proprietary (you created it)' vs 'Product-derived' distinction in data hierarchy could be clearer with examples
Model: claude-haiku-4-5-20251001Analyzed: Jun 28, 2026

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Version History

v1.2

Content updated

2026-06-28

Latest
v1.1

Content updated

2026-04-20

v1.0

No changelog

2026-04-19

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