| name | programmatic-seo |
| description | Plan or audit SEO pages generated at scale from structured data — data-source quality, template uniqueness, URL patterns, internal linking, canonicals, sitemaps, and index-bloat prevention — enforcing hard quality gates against thin content and Google's Scaled Content Abuse policy (uniqueness thresholds, batch rollout limits, standalone value test). Produces a /100 scorecard with prioritized fixes and a progressive rollout plan. Triggers on "/digital-marketing-pro:programmatic-seo", "plan programmatic landing pages", "audit our location pages", "will 5000 generated pages get us penalized", "design a template engine for pSEO". Reads the brand profile and guidelines; plans and audits only — it does not generate or publish the pages. |
| argument-hint | [URL or plan] |
| user-invocable | true |
/digital-marketing-pro:programmatic-seo
Purpose
Plan and audit SEO pages generated at scale from structured data sources (databases, APIs, CSV/JSON files). Enforces quality gates to prevent thin content penalties, index bloat, and Google's Scaled Content Abuse policy.
Input Required
The user must provide (or will be prompted for):
- URL or data source: Existing programmatic pages to audit, or data source details for planning
- Page type: What kind of pages are being generated (location, product, integration, glossary, template, tool)
- Data source: CSV/JSON files, API endpoints, database queries — or existing pages to analyze
- Target scale: How many pages will be generated
- Current status: New build or auditing existing programmatic pages
Process
- Load brand context: Read
~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply industry context and compliance rules. Check for brand guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json.
- Data source assessment: Evaluate the data powering programmatic pages — row count, column uniqueness, missing values, duplicate detection (>80% field overlap), data freshness
- Template engine planning: Design templates that produce genuinely unique pages — variable injection points, content blocks (static vs dynamic), conditional logic, supplementary content. Validate each page passes the "standalone value test"
- URL pattern strategy: Design URL hierarchy — lowercase hyphenated slugs, logical structure, uniqueness enforcement, under 100 characters, consistent trailing slash
- Internal linking automation: Hub/spoke model, related items (3-5 per page), breadcrumbs with BreadcrumbList schema, cross-linking by shared attributes, varied anchor text
- Thin content safeguard check: Apply quality gates (see below)
- Canonical strategy: Self-referencing canonicals, parameter handling, pagination strategy, manual page priority
- Sitemap integration: Auto-generate entries, split at 50K URLs,
<lastmod> from actual data timestamps, exclude noindexed pages
- Index bloat prevention: Noindex low-value pages, pagination handling, faceted navigation canonicalization, crawl budget monitoring for 10K+ pages
- Score and report: Score each dimension, produce prioritized action plan
Quality Gates
Scale Thresholds
| Metric | Threshold | Action |
|---|
| Pages without content review | 100+ | WARNING: require content audit before publishing |
| Pages without justification | 500+ | HARD STOP: require explicit user approval and thin content audit |
| Unique content per page | <40% | Flag as thin content (penalty risk) |
| Unique content per page | <30% | HARD STOP: scaled content abuse risk |
| Word count per page | <300 | Flag for review (may lack sufficient value) |
Scaled Content Abuse Context (2025-2026)
Google's Scaled Content Abuse policy (introduced March 2024) saw major enforcement escalation:
- June 2025: Wave of manual actions targeting AI-generated content at scale
- August 2025: SpamBrain update enhanced pattern detection for AI-generated link schemes and content farms
- Result: 45% reduction in low-quality, unoriginal content in search results
Enhanced quality gates for programmatic pages:
- Content differentiation: 30-40%+ of content must be genuinely unique between any two programmatic pages (not just city/keyword string replacement)
- Human review: Minimum 5-10% sample review of generated pages before publishing
- Progressive rollout: Publish in batches of 50-100 pages. Monitor indexing and rankings for 2-4 weeks before expanding. Never publish 500+ simultaneously without quality review.
- Standalone value test: Each page should pass: "Would this page be worth publishing even if no other similar pages existed?"
- Site reputation abuse: Publishing programmatic content under a high-authority domain (not your own) may trigger site reputation abuse penalties (enforced aggressively since November 2024)
Safe vs Risky Programmatic Pages
Safe at scale:
- Integration pages (with real setup docs, API details, screenshots)
- Template/tool pages (with downloadable content, usage instructions)
- Glossary pages (200+ word definitions with examples, related terms)
- Product pages (unique specs, reviews, comparison data)
- Data-driven pages (unique statistics, charts, analysis per record)
Penalty risk at scale:
- Location pages with only city name swapped in identical text
- "Best [tool] for [industry]" without industry-specific value
- "[Competitor] alternative" without real comparison data
- AI-generated pages without human review and unique value-add
- Pages where >60% of content is shared template boilerplate
Uniqueness Calculation
Unique content % = (words unique to this page) / (total words on page) x 100
Measured against all other pages in the programmatic set. Shared headers, footers, and navigation excluded. Template boilerplate IS included.
URL Pattern Library
Common Patterns
/tools/[tool-name]: Tool/product directory pages/[city]/[service]: Location + service pages/integrations/[platform]: Integration landing pages/glossary/[term]: Definition/reference pages/templates/[template-name]: Downloadable template pages/compare/[product-a]-vs-[product-b]: Comparison pages
URL Rules
- Lowercase, hyphenated slugs derived from data
- Logical hierarchy reflecting site architecture
- No duplicate slugs — enforce uniqueness at generation time
- Keep URLs under 100 characters
- No query parameters for primary content URLs
- Consistent trailing slash usage (match existing site pattern)
Output
A structured programmatic SEO assessment containing:
Programmatic SEO Score: XX/100
| Category | Status | Score |
|---|
| Data Quality | score | /100 |
| Template Uniqueness | score | /100 |
| URL Structure | score | /100 |
| Internal Linking | score | /100 |
| Thin Content Risk | score | /100 |
| Index Management | score | /100 |
- Critical issues (fix immediately)
- High priority (fix within 1 week)
- Medium priority (fix within 1 month)
- Recommendations: data source improvements, template modifications, URL pattern adjustments, quality gate compliance actions
- Progressive rollout plan with batch sizes and monitoring checkpoints
Agents Used
- seo-specialist — Programmatic page analysis, quality gate enforcement, URL strategy, template evaluation
- content-creator — Template content design, uniqueness optimization
Scripts Used
- tech-seo-auditor.py — Check technical SEO issues across programmatic page samples
- content-scorer.py — Score content quality and uniqueness per template
- competitor-scraper.py — Analyze competitor programmatic page patterns
