SkillAgentSearch skills...

programmatic-seo

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 thresh…

Install / Use

npx skills add indranilbanerjee/digital-marketing-pro --skill programmatic-seo

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

84/100

Category

Marketing

Supported Platforms

Zed

Our assessment of programmatic-seo

programmatic-seo scores 84/100 on our quality scale, 411th of 610 Marketing skills we index.

Its SKILL.md is 7.6 KB long, well organised into 16 sections and no code examples: a thorough specification that gives an agent plenty to work with.

It has 832 GitHub stars, a meaningful sign that others use it.

Substance
29/30
Structure
13/20
Description
15/15
Adoption
12/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 26 days ago, so programmatic-seo is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

programmatic-seo compared with similar skills

All 4 of these similar skills score higher than programmatic-seo; compare them before choosing.

SkillScoreStarsUpdatedFormat
programmatic-seo (this skill)by indranilbanerjee8483226d agoSKILL.md
Agent-Reachby Panniantong10090.1k18d agoCLAUDE.md
algorithmic-artby anthropics100177.9k11d agoSKILL.md
pptxby anthropics100177.9k11d agoSKILL.md
designby nextlevelbuilder100130.2k12d agoSKILL.md

Frequently asked questions

How do I install programmatic-seo?
Run npx skills add indranilbanerjee/digital-marketing-pro --skill programmatic-seo. The install tabs above show the steps for each supported agent.
Which AI agents does programmatic-seo work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is programmatic-seo safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is programmatic-seo still maintained?
The repository was last updated 26 days ago, so programmatic-seo is actively maintained.

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

  1. 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.
  2. Data source assessment: Evaluate the data powering programmatic pages — row count, column uniqueness, missing values, duplicate detection (>80% field overlap), data freshness
  3. 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"
  4. URL pattern strategy: Design URL hierarchy — lowercase hyphenated slugs, logical structure, uniqueness enforcement, under 100 characters, consistent trailing slash
  5. Internal linking automation: Hub/spoke model, related items (3-5 per page), breadcrumbs with BreadcrumbList schema, cross-linking by shared attributes, varied anchor text
  6. Thin content safeguard check: Apply quality gates (see below)
  7. Canonical strategy: Self-referencing canonicals, parameter handling, pagination strategy, manual page priority
  8. Sitemap integration: Auto-generate entries, split at 50K URLs, <lastmod> from actual data timestamps, exclude noindexed pages
  9. Index bloat prevention: Noindex low-value pages, pagination handling, faceted navigation canonicalization, crawl budget monitoring for 10K+ pages
  10. 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

Related Skills

View on GitHub
GitHub Stars832
CategoryMarketing
Updated26d ago
Forks136

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions