| name | seo-programmatic |
| description | Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", or "data-driven SEO".
|
| user-invokable | true |
| argument-hint | [url or plan] |
| license | MIT |
| metadata | {"author":"dotusmanali","version":"2.0.0","category":"seo"} |
| id | seo-programmatic |
| domain | content |
| invoked_by | ["seo-content","seo-programmatic","seo"] |
| depends_on | [] |
Programmatic SEO Analysis & Planning
Shared Data Cache
Step 0 -- Check shared data cache:
Before gathering, check .seo-cache/ for reusable context from related SEO skills.
Reference: ../seo/references/shared-data-cache.md for schemas and dependency map.
Check these cache files when present:
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.seo-cache/site-meta.json for domain, business type, industry, and crawl context
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.seo-cache/audit-scores.json for prior full-audit priorities
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.seo-cache/pages/{url-slug}/page-analysis.json for page-level context when a URL is provided
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If found: parse and use clearly valid fields (note "Using cached [X] from [date]")
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If missing, corrupt, or irrelevant: continue with fresh evidence
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If the user says "refresh" or "re-run": ignore cache reads and overwrite on write
Build and audit SEO pages generated at scale from structured data sources.
Enforces quality gates to prevent thin content penalties and index bloat.
Data Source Assessment
Evaluate the data powering programmatic pages:
- CSV/JSON files: Row count, column uniqueness, missing values
- API endpoints: Response structure, data freshness, rate limits
- Database queries: Record count, field completeness, update frequency
- Data quality checks:
- Each record must have enough unique attributes to generate distinct content
- Flag duplicate or near-duplicate records (>80% field overlap)
- Verify data freshness; stale data produces stale pages
Template Engine Planning
Design templates that produce unique, valuable pages:
- Variable injection points: Title, H1, body sections, meta description, schema
- Content blocks: Static (shared across pages) vs dynamic (unique per page)
- Conditional logic: Show/hide sections based on data availability
- Supplementary content: Related items, contextual tips, user-generated content
- Template review checklist:
- Each page must read as a standalone, valuable resource
- No "mad-libs" patterns (just swapping city/product names in identical text)
- Dynamic sections must add genuine information, not just keyword variations
