Programmatic SEO Planner

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_content.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-post-finder to find how ICP talks about the problem:

python3 skills/reddit-post-finder/scripts/search_reddit.py \
  --subreddit "<relevant_subs>" \
  --keywords "<category>,<problem keyword>" \
  --days 365 --sort top --time year

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