Programmatic SEO Page Planner

Programmatic SEO is how startups generate hundreds of high-intent pages from templates — "{Your Product} vs {Competitor}", "Best {Category} for {Industry}", "{Integration} + {Your Product}". This skill figures out which patterns are worth building, designs the templates, and prioritizes the buildout.

Core principle: pSEO isn't about spinning content. It's about finding a data axis (something that varies per page) where each variation has real search demand and your product has a genuine answer. This skill validates both before you invest in building.

When to Use

• "How do we scale SEO pages without writing each one manually?"
• "Should we build vs/ comparison pages?"
• "What programmatic SEO patterns work for SaaS?"
• "How can we rank for hundreds of long-tail keywords?"
• "Plan our pSEO strategy"

Tool Enhancement (Optional)

This skill works with existing capabilities but produces significantly better results when paired with a keyword data API for bulk volume lookups across hundreds of long-tail variations.

Agent Prompt to User

"I can plan your programmatic SEO strategy using our existing tools. However, for the best results — especially accurate search volume data across hundreds of keyword variations — I'd recommend connecting a keyword data API."

Recommended: DataForSEO (pay-per-use, ~$0.01/keyword, no monthly minimum)

• Sign up at dataforseo.com → get API login + password
• Set DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD env vars

Alternatives that also work:

• Keywords Everywhere API ($1 per 10 credits = 100K keywords, very cheap) → set KEYWORDS_EVERYWHERE_API_KEY
• SEMrush API (if you have a subscription) → set SEMRUSH_API_KEY
• Ahrefs API (if you have a subscription) → set AHREFS_API_TOKEN

"Want to use one of these, or should I proceed with baseline mode? Baseline still works — I'll use our Apify-based SEO tools for top-level data, though volume estimates for individual long-tail patterns will be less precise."

Mode Selection

• Enhanced mode — Bulk keyword volume lookups via DataForSEO / Keywords Everywhere / SEMrush / Ahrefs. Gets exact monthly search volume, keyword difficulty, and CPC for each pattern variation. Enables confident prioritization.
• Baseline mode — Uses seo-domain-analyzer (Apify) for domain-level metrics and web_search for pattern validation. Volume estimates are directional, not exact. Still produces a solid blueprint — just less granular on per-variation demand.

Phase 0: Intake

1. Your product — URL + one-sentence description
2. Category — What category/market do you play in?
3. Competitors — 3-5 competitor URLs (we'll analyze their pSEO plays)
4. ICP — Who's searching for your product? (roles, industries, company stages)
5. Existing content — Do you already have a blog/resource section? (URL if yes)
6. CMS/tech stack — What powers your site? (Webflow, WordPress, Next.js, etc.) — informs template feasibility
7. Tool preference — Enhanced mode with keyword API, or baseline? (see Tool Enhancement above)

Phase 1: Pattern Discovery

1A: Competitor pSEO Analysis

Run site-content-catalog for each competitor:

python3 skills/site-content-catalog/scripts/catalog_site.py \
  --url "<competitor_url>" \
  --output json

Analyze URL structures for programmatic patterns:

• /vs/, /compare/, /alternatives/ — Comparison pages
• /integrations/, /connect/, /apps/ — Integration pages
• /for-{industry}/, /solutions/, /use-cases/ — Vertical/use-case pages
• /templates/, /examples/, /glossary/ — Resource pages
• /tools/, /calculators/, /generators/ — Tool pages

For each pattern found, note:

• URL pattern (regex)
• Estimated page count
• What varies per page (the "data axis")
• Sample page titles

1B: Market Pattern Mapping

Based on your product category, evaluate these standard pSEO pattern types:

1C: Customer Language Mining

Run reddit-scraper to find how ICP talks about the problem:

python3 skills/reddit-scraper/scripts/scrape_reddit.py \
  --query "<category> OR <problem keyword>" \
  --subreddits "<relevant_subs>" \
  --sort relevance --time year --limit 50

Extract:

• Questions people ask → potential glossary/guide patterns
• "How do I [X] with [tool]?" → integration/use-case patterns
• "Is there a [X] for [industry]?" → vertical page patterns
• Comparison discussions → vs/ page patterns

1D: Keyword Volume Validation

Enhanced mode (DataForSEO / Keywords Everywhere / SEMrush / Ahrefs):

For each candidate pattern, generate 20-50 keyword variations and pull exact volumes:

• "your-product vs {competitor1}", "your-product vs {competitor2}", etc.
• "best {category} for {industry1}", "best {category} for {industry2}", etc.
• "{your-product} {integration1} integration", etc.

Aggregate per pattern type:

• Total addressable monthly searches across all variations
• Average volume per variation
• Volume distribution (are a few variations high-volume or is it evenly spread?)
• Average keyword difficulty

Baseline mode:

Use seo-domain-analyzer for competitor domain metrics, web_search to spot-check if key variations have SERP results (indicating real demand), and manual estimation based on:

• Competitor page count per pattern (more pages = likely more demand)
• Google autocomplete suggestions for pattern variations
• Reddit/community question frequency

Phase 2: Pattern Evaluation

Score each candidate pattern on:

Score each pattern 0-100. Rank by score.

Feasibility Check Per Pattern

For each pattern scoring 50+, validate:

1. Data source — Where does the variable data come from?

   • Competitor names → manual list (finite, high-value)
   • Integration/tool names → API marketplace, app directory
   • Industry names → standard industry lists
   • Terms/glossary → keyword research output
   • Templates → product feature matrix

2. Content differentiation — Can each page offer genuine value, or will they be thin?

   • vs/ pages need real feature comparisons, not just "we're better"
   • Integration pages need actual setup guides or use cases
   • Vertical pages need industry-specific pain points and examples

3. Technical feasibility — Can your CMS generate these at scale?

   • Static site generators (Next.js, Astro) → excellent for pSEO
   • Webflow CMS → good, max 10K items per collection
   • WordPress → good with custom post types
   • Manual creation → not pSEO, just a lot of pages

Phase 3: Template Design

For each pattern being built, design:

Template Blueprint

## Pattern: [vs/{competitor}]
 
### URL Structure
/vs/{competitor-slug}
 
### Title Template
{Your Product} vs {Competitor} — [Year] Comparison | {Your Brand}
 
### Meta Description Template
Compare {Your Product} and {Competitor} side-by-side. See pricing, features,
pros/cons, and which is better for {ICP description}.
 
### H1
{Your Product} vs {Competitor}: Honest Comparison
 
### Page Sections (content framework)
1. **TL;DR** — 3-sentence summary of key differences (above fold)
2. **Quick comparison table** — Feature matrix with checkmarks
3. **Detailed comparison** — 4-6 key dimensions, 2-3 paragraphs each
4. **Pricing comparison** — Plan-by-plan breakdown
5. **Who should choose {Your Product}** — ICP fit description
6. **Who should choose {Competitor}** — Fair assessment
7. **What real users say** — Review quotes from both sides
8. **CTA** — Trial/demo prompt
 
### Data Required Per Page
- competitor_name: string
- competitor_slug: string
- competitor_features: array (from their website/docs)
- competitor_pricing: object (from pricing page)
- competitor_reviews: array (from G2/Capterra)
- your_differentiators: array (per competitor)
 
### Content Guidelines
- Minimum 1,500 words per page
- Must include at least one unique insight (not just feature lists)
- Use actual screenshots or diagrams where possible
- Update quarterly (pricing/features change)

Repeat for each pattern type.

Phase 4: Prioritization & Roadmap

Build the implementation plan:

Priority Matrix

Recommended Buildout Sequence

Month 1: Quick wins

• Build [pattern A] — [X] pages, [rationale]
• Build [pattern B] — [X] pages, [rationale]

Month 2: Scale

• Build [pattern C] — [X] pages, [rationale]
• Measure Month 1 patterns, iterate templates

Month 3: Expand

• Build [pattern D] — [X] pages, [rationale]
• Update Month 1 pages with performance data

Per-Pattern Data Source Plan

For each pattern, specify exactly where the variable data comes from:

• Manual curation (competitors list — finite, high quality)
• API source (integration marketplace)
• Scraping (review sites, competitor pages)
• Internal data (product features, pricing)

Phase 5: Output

# Programmatic SEO Blueprint — [Product Name] — [DATE]
 
## Executive Summary
- [N] patterns evaluated, [M] recommended for buildout
- Total addressable search volume: [X]/month
- Estimated pages to build: [Y]
- Recommended buildout timeline: [Z] months
 
---
 
## Pattern Analysis (ranked by priority)
 
### P0: [Pattern Name]
- URL structure: [pattern]
- Pages to build: [N]
- Total monthly volume: [X]
- Template blueprint: [see below]
- Data source: [where variable data comes from]
- Build effort: [Low/Medium/High]
- Expected time to rank: [2-4 months / 4-8 months / etc.]
 
[Full template blueprint per Phase 3]
 
### P1: [Pattern Name]
...
 
---
 
## Technical Requirements
- CMS: [capabilities needed]
- Data pipeline: [how to source variable data]
- Update cadence: [how often to refresh]
 
---
 
## Quick-Start Guide
1. Start with [pattern] — lowest effort, highest intent
2. Create [N] pages using the template above
3. Monitor for [X] weeks before expanding
4. ...

Save to clients/<client-name>/seo/pseo-blueprint-[YYYY-MM-DD].md.

Cost

Tools Required

• Apify API token — APIFY_API_TOKEN env var
• Upstream skills: site-content-catalog, seo-domain-analyzer, reddit-scraper
• Optional (enhanced): DataForSEO (DATAFORSEO_LOGIN + DATAFORSEO_PASSWORD), Keywords Everywhere (KEYWORDS_EVERYWHERE_API_KEY), SEMrush (SEMRUSH_API_KEY), or Ahrefs (AHREFS_API_TOKEN)

Trigger Phrases

• "Plan our programmatic SEO strategy"
• "What pSEO pages should we build?"
• "Design vs/ comparison pages for our product"
• "How do we scale to hundreds of SEO pages?"
• "Build a pSEO blueprint for [client]"
• "What programmatic patterns should we use?"