seo-programmatic▌
agricidaniel/claude-seo · updated Apr 16, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Build and audit SEO pages generated at scale from structured data sources.
- ›Enforces quality gates to prevent thin content penalties and index bloat.
Programmatic SEO Analysis & Planning
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
URL Pattern Strategy
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
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)
Internal Linking Automation
- Hub/spoke model: Category hub pages linking to individual programmatic pages
- Related items: Auto-link to 3-5 related pages based on data attributes
- Breadcrumbs: Generate BreadcrumbList schema from URL hierarchy
- Cross-linking: Link between programmatic pages sharing attributes (same category, same city, same feature)
- Anchor text: Use descriptive, varied anchor text. Avoid exact-match keyword repetition
- Link density: 3-5 internal links per 1000 words (match seo-content guidelines)
Thin Content Safeguards
Quality Gates
| 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 (likely penalty risk) |
| Word count per page | <300 | ⚠️ Flag for review (may lack sufficient value) |
Scaled Content Abuse: Enforcement Context (2025-2026)
Google's Scaled Content Abuse policy (introduced March 2024) saw major enforcement escalation in 2025:
- June 2025: Wave of manual actions targeting websites with AI-generated content at scale
- August 2025: SpamBrain spam update enhanced pattern detection for AI-generated link schemes and content farms
- Result: Google reported 45% reduction in low-quality, unoriginal content in search results post-March 2024 enforcement
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+ programmatic pages simultaneously without explicit 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: If publishing programmatic content under a high-authority domain (not your own), this may trigger site reputation abuse penalties. Google began enforcing this aggressively in November 2024.
Recommendation: The WARNING gate at
<40% unique contentremains appropriate. Consider a HARD STOP at<30%unique content to prevent scaled content abuse risk.
Safe Programmatic Pages (OK 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 (avoid 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) × 100
Measure against all other pages in the programmatic set. Shared headers, footers, and navigation are excluded from the calculation. Template boilerplate text IS included.
Canonical Strategy
- Every programmatic page must have a self-referencing canonical tag
- Parameter variations (sort, filter, pagination) canonical to the base URL
- Paginated series: canonical to page 1 or use rel=next/prev
- If programmatic pages overlap with manual pages, the manual page is canonical
- No canonical to a different domain unless intentional cross-domain setup
Sitemap Integration
- Auto-generate sitemap entries for all programmatic pages
- Split at 50,000 URLs per sitemap file (protocol limit)
- Use sitemap index if multiple sitemap files needed
<lastmod>reflects actual data update timestamp (not generation time)- Exclude noindexed programmatic pages from sitemap
- Register sitemap in robots.txt
- Update sitemap dynamically as new records are added to data source
Index Bloat Prevention
- Noindex low-value pages: Pages that don't meet quality gates
- Pagination: Noindex paginated results beyond page 1 (or use rel=next/prev)
- Faceted navigation: Noindex filtered views, canonical to base category
- Crawl budget: For sites with >10k programmatic pages, monitor crawl stats in Search Console
- Thin page consolidation: Merge records with insufficient data into aggregated pages
- Regular audits: Monthly review of indexed page count vs intended count
Output
Programmatic SEO Score: XX/100
Assessment Summary
| Category | Status | Score |
|---|---|---|
| Data Quality | ✅/⚠️/❌ | XX/100 |
| Template Uniqueness | ✅/⚠️/❌ | XX/100 |
| URL Structure | ✅/⚠️/❌ | XX/100 |
| Internal Linking | ✅/⚠️/❌ | XX/100 |
| Thin Content Risk | ✅/⚠️/❌ | XX/100 |
| Index Management | ✅/⚠️/❌ | XX/100 |
Critical Issues (fix immediately)
High Priority (fix within 1 week)
Medium Priority (fix within 1 month)
Low Priority (backlog)
Recommendations
- Data source improvements
- Template modifications
- URL pattern adjustments
- Quality gate compliance actions
Error Handling
| Scenario | Action |
|---|---|
| URL unreachable | Report connection error with status code. Suggest verifying URL accessibility and checking for authentication requirements. |
| No programmatic pages detected | Inform user that no template-generated or data-driven page patterns were found. Suggest checking if pages use client-side rendering or if the URL points to the correct section. |
| Thin content threshold exceeded | Trigger quality gate warning. Report the unique content percentage and flag pages below 40% uniqueness. Require user acknowledgment before proceeding. |
| Quality gate violation | Halt analysis at the HARD STOP threshold (500+ pages without justification or <30% unique content). Present findings and require explicit user approval to continue. |
How to use seo-programmatic on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add seo-programmatic
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches seo-programmatic from GitHub repository agricidaniel/claude-seo and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate seo-programmatic. Access the skill through slash commands (e.g., /seo-programmatic) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★53 reviews- ★★★★★Olivia Farah· Dec 8, 2024
Registry listing for seo-programmatic matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yusuf Diallo· Dec 8, 2024
seo-programmatic fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Hassan Taylor· Dec 8, 2024
seo-programmatic reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Daniel Sethi· Dec 4, 2024
I recommend seo-programmatic for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yusuf Rahman· Nov 27, 2024
We added seo-programmatic from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★William Sanchez· Nov 23, 2024
Solid pick for teams standardizing on skills: seo-programmatic is focused, and the summary matches what you get after install.
- ★★★★★Daniel Taylor· Nov 15, 2024
Useful defaults in seo-programmatic — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Fatima Rahman· Oct 18, 2024
seo-programmatic reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Amelia Garcia· Oct 18, 2024
seo-programmatic fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★William Ndlovu· Oct 14, 2024
seo-programmatic is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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