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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," "templated landing pages," or "which CMS for pSEO." 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.

NewUpdated Oct 7, 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

6. Choose the Build Platform

Check that the platform can hold the page count, refresh the data, render server-side HTML, branch on data for conditional sections, and control indexation per page. Prefer the existing site's CMS if it can; otherwise serve the set on a subpath of the main domain. Options and tradeoffs: references/implementation-platforms.md.


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
Files4
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Overall Score

88/100

Grade

A

Excellent

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

92

Quality

87

Clarity

86

Completeness

83

Summary

This skill teaches AI agents how to build SEO-optimized pages at scale using templating and data—the core practice of programmatic SEO. It provides a structured framework covering 12 proven playbooks (Templates, Curation, Comparisons, Locations, Personas, Integrations, Glossary, Translations, Directory, Profiles, Conversions, Examples), core principles (unique value, proprietary data, clean URLs), and implementation guidance (keyword research, data requirements, template design, internal linking, indexation). The skill is operationalized through an assessment phase, a decision matrix for choosing playbooks, and detailed implementation steps with quality checks and common pitfalls.

Detected Capabilities

read files (product-marketing context)provide structured templates and frameworksrecommend implementation platformsaudit and validate strategy planningcross-reference related skills

Trigger Keywords

Phrases that agents use to match this skill to user intent.

create scaled pagesprogrammatic seo strategylocation pagescomparison pagestemplate pagesdata-driven pagespseo playbooksintegration pagessite scale-up

Referenced Domains

External domains referenced in skill content, detected by static analysis.

github.com

Use Cases

  • Plan and validate programmatic SEO strategies before building pages
  • Design scalable page templates for 'X in Y' location pages and other patterns
  • Identify which playbook fits your product and assets
  • Structure data and internal linking for thousands of similar pages
  • Avoid thin content penalties by ensuring unique value per page
  • Choose between CMS platforms for holding large-scale page sets
  • Diagnose indexation issues in programmatic page launches
  • Map keyword patterns to data sources for layered playbook combinations

Quality Notes

  • Excellent scope clarity: the skill explicitly defers technical SEO audits to the seo-audit skill and content strategy to content-strategy, establishing clear boundaries.
  • Comprehensive reference material: two supporting docs (playbooks.md, implementation-platforms.md) provide deep practical guidance without bloating the main SKILL.md.
  • Strong structure: 12 playbooks presented as a discoverable decision tree with asset-matching table, enabling flexible combinations.
  • Platform tradeoffs explicitly documented: the implementation-platforms.md compares item limits, data refresh, conditional logic, and publish performance across 6 major options—critical for 1000+ page launches.
  • Detailed eval set (7 test cases) covers diverse scenarios: persona pages, competitor comparisons, integrations, indexation diagnosis, glossary, technical audits, and platform selection. Assertions are specific and validate expected reasoning.
  • Clear warnings on common mistakes: thin content, keyword cannibalization, over-generation, data quality, UX-ignoring—each rooted in real programmatic SEO failure modes.
  • Pre-flight context check: skill recommends reading product-marketing.md or legacy filenames first, reducing redundant questioning.
  • Quality checklist provided: pre-launch and post-launch monitoring with specific metrics (indexation rate, rankings, traffic, engagement, conversion) and warning signs (thin content warnings, ranking drops, manual actions).
Model: claude-haiku-4-5-20251001Analyzed: Oct 7, 2026

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Version History

  1. v2.0

    Contract changed: description

    ✦ AIAdds platform selection guidance and new reference document for programmatic SEO implementation choices.

    triggering2026-10-07

    LATEST
  2. v1.2

    Content updated

    ✦ AIUpdated file path patterns for product marketing context and renamed related skills (schema-markup → schema; competitor-alternatives → competitors

    2026-06-28

    View This Version
  3. v1.1

    Content updated

    ✦ AIAdds evaluation suite and reference playbooks.

    2026-04-20

    View This Version
  4. v1.0

    2026-04-19

    View This VersionInitial version

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