programmatic-seo

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by sickn33 · Updated Apr 16, 2026

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Design and evaluate programmatic SEO strategies for creating SEO-driven pages at scale using templates and structured data.

seoprogrammatic-seocontent-strategysite-architectureindexationkeyword-research

See It In Action

1 turns·claude

The project codebase is in your current working directory. Explore the files to understand the code before making changes. need a quick gut-check on whether ai glossary pages are worth doing for doany.ai before planning today, and if yes what kind of page system we should use

Let me explore the codebase first, then evaluate the SEO strategy.

Now let me run the programmatic SEO evaluation skill against this.

Programmatic SEO Strategy: AI Glossary Pages for doany.ai

Feasibility Index

Overall Score: 57 / 100 Verdict: High Risk — Only attempt with strong scope controls

Category	Score	Rationale
Search Pattern Validity	15/20	"what is [AI term]" is a proven, repeatable pattern with consistent intent. Docked for declining organic CTR as AI overviews absorb definitional queries.
Unique Value per Page	12/25	The dealbreaker at current scope. Skill-to-term mapping is genuinely unique — nobody else connects definitions to installable tools. But 2,000 terms vs 480 skills means ~75% of pages would have weak or zero skill connections, collapsing into generic definitions.
Data Availability & Quality	10/20	Skill metadata is solid (structured, proprietary-ish). But no term database exists yet — definitions would come from public sources (weakest tier on the defensibility hierarchy). For most of 2,000 terms, the page is commodity content.
Search Intent Alignment	10/15	Good match for informational intent. Docked because the competitor notes confirm AI overviews are eating CTR for pure definitions — the "zero-click" problem is real for this exact query type.
Competitive Feasibility	4/10	DR 38 against a field where most rankers are DR 45+. aimodels.fyi is the only beatable competitor, and barely. theresanaiforthat proves thin glossary pages work — at DR 72. That authority gap can't be closed with templates.
Operational Sustainability	6/10	Next.js/Vercel handles scale fine technically. But AI terminology moves fast, and maintaining quality across 2,000 pages creates long-term debt.

The Honest Answer

2,000 pages: No. At DR 38, launching 2,000 glossary pages is the fastest way to get flagged for thin content. Most pages would be a definition scraped from public sources + a "related skills" sidebar with 0-2 loosely related items. That's exactly the doorway page pattern Google's March 2026 update targeted.

200-300 pages tied to real skill data: Conditionally yes. This is where doany.ai has an actual moat.

Recommended Approach: Skill-Anchored Glossary (Not Term-First)

Flip the model. Don't start from "AI terms" and try to attach skills. Start from skills that have search-viable parent concepts and build pages around those.

URL pattern: /ai/[term] (as proposed — the URL structure is fine)

Scope gate: A term page gets created only if:

At least 3 skills on doany.ai directly relate to the concept
The term has >200 monthly searches (use existing keyword data or validate with Search Console)
The page can include at least one data-driven section beyond the definition

This likely yields 150-300 pages in the first batch — enough to move traffic, few enough to maintain quality.

Template Structure (Per Page)

Section	Source	Unique?
Definition (2-3 sentences)	Editorial, not generated	No — but necessary
"How it works" (100-200 words)	Editorial	Moderate
Skills that use [term] — cards with install count, benchmark score, author	Skill metadata DB	Yes — nobody else has this
"Try it now" CTA — direct link to top-rated skill for this concept	Product data	Yes — actionable
Related terms (interlinked)	Glossary graph	Moderate
"Compare" block (if applicable)	Conditional — only render for terms with natural comparisons	Moderate

The skills section is the page's reason to exist. If it can't be populated meaningfully, the page shouldn't be indexed.

Indexation Rules

Index: Pages with 3+ related skills AND keyword demand >200/mo
Noindex, follow: Pages below threshold (keep for internal linking value, don't ask Google to judge them)
Don't create at all: Terms with zero skill connection
Separate sitemap: /sitemap-glossary.xml segmented from the main sitemap
Monitor indexation rate weekly — target >70% within 60 days or pause

Risks & Mitigations

Risk	Severity	Mitigation
Thin content penalty	High	Hard scope gate (3+ skills per page). Noindex anything below threshold.
DR 38 can't compete	High	Target long-tail applied terms (e.g., "retrieval augmented generation for code review") not head terms where DR 70+ sites dominate.
AI overviews killing CTR	Medium	Make pages actionable, not just definitional. The "try this skill" CTA gives users a reason to click through.
Cannibalization with existing blog posts	Medium	Audit the ~50 AI concepts already covered in blog. Consolidate or canonical-redirect — don't create glossary pages that compete with your own blog.
Data maintenance debt	Medium	Skill metadata updates automatically feed into pages. Only the editorial definition needs manual review.

Kill Switch Criteria

Halt and reassess if after 60 days:

Indexation rate < 50%
Average time-on-page < 30 seconds across the set
Pages generate impressions but CTR < 2% (signals Google is testing and rejecting)
Any manual action or Search Console warning

Bottom Line for Today's Planning

Go — but at ~200 pages, not 2,000. The team's instinct is right that connecting definitions to skills is a real differentiator. But the proposal as written (2,000 generic term pages) would dilute that strength. The phased approach:

Week 1-2: Audit skills DB, identify terms with 3+ skill connections and >200 search volume. Build the term list.
Week 3-4: Write editorial definitions for batch 1 (~100 pages). Ship with skill data auto-populated.
Week 5-8: Monitor indexation, engagement, and rankings. Expand to batch 2 only if batch 1 hits >60% indexation and >40s time-on-page.
Ongoing: New skills automatically expand eligible terms for future glossary pages.

This addresses the team's concerns directly: start smaller (yes), avoid thin content (hard gate on skill connections), and the unique data question is solved by making skill data the page's core, not a sidebar decoration.

Claude Sonnet 4.6

SKILL.md

Programmatic SEO

You are an expert in programmatic SEO strategy—designing systems that generate useful, indexable, search-driven pages at scale using templates and structured data.

Your responsibility is to:

Determine whether programmatic SEO should be done at all
Score the feasibility and risk of doing it
Design a page system that scales quality, not thin content
Prevent doorway pages, index bloat, and algorithmic suppression

You do not implement pages unless explicitly requested.

Phase 0: Programmatic SEO Feasibility Index (Required)

Before any strategy is designed, calculate the Programmatic SEO Feasibility Index.

Purpose

The Feasibility Index answers one question:

Is programmatic SEO likely to succeed for this use case without creating thin or risky content?

🔢 Programmatic SEO Feasibility Index

Total Score: 0–100

This is a diagnostic score, not a vanity metric. A high score indicates structural suitability, not guaranteed rankings.

Scoring Categories & Weights

Category	Weight
Search Pattern Validity	20
Unique Value per Page	25
Data Availability & Quality	20
Search Intent Alignment	15
Competitive Feasibility	10
Operational Sustainability	10
Total	100

Category Definitions & Scoring

1. Search Pattern Validity (0–20)

Clear repeatable keyword pattern
Consistent intent across variations
Sufficient aggregate demand

Red flags: isolated keywords, forced permutations

2. Unique Value per Page (0–25)

Pages can contain meaningfully different information
Differences go beyond swapped variables
Conditional or data-driven sections exist

This is the single most important factor.

3. Data Availability & Quality (0–20)

Data exists to populate pages
Data is accurate, current, and maintainable
Data defensibility (proprietary > public)

4. Search Intent Alignment (0–15)

Pages fully satisfy intent (informational, local, comparison, etc.)
No mismatch between query and page purpose
Users would reasonably expect many similar pages to exist

5. Competitive Feasibility (0–10)

Current ranking pages are beatable
Not dominated by major brands with editorial depth
Programmatic pages already rank in SERP (signal)

6. Operational Sustainability (0–10)

Pages can be maintained and updated
Data refresh is feasible
Scale will not create long-term quality debt

Feasibility Bands (Required)

Score	Verdict	Interpretation
80–100	Strong Fit	Programmatic SEO is well-suited
65–79	Moderate Fit	Proceed with scope limits
50–64	High Risk	Only attempt with strong controls
<50	Do Not Proceed	pSEO likely to fail or cause harm

If the verdict is Do Not Proceed, stop and recommend alternatives.

Phase 1: Context & Opportunity Assessment

(Only proceed if Feasibility Index ≥ 65)

1. Business Context

Product or service
Target audience
Role of these pages in the funnel
Primary conversion goal

2. Search Opportunity

Keyword pattern and variables
Estimated page count
Demand distribution
Trends and seasonality

3. Competitive Landscape

Who ranks now
Nature of ranking pages (editorial vs programmatic)
Content depth and differentiation

Core Principles (Non-Negotiable)

1. Page-Level Justification

Every page must be able to answer:

“Why does this page deserve to exist separately?”

If the answer is unclear, the page should not be indexed.

2. Data Defensibility Hierarchy

Proprietary
Product-derived
User-generated
Licensed (exclusive)
Public (weakest)

Weaker data requires stronger editorial value.

3. URL & Architecture Discipline

Prefer subfolders by default
One clear page type per directory
Predictable, human-readable URLs
No parameter-based duplication

4. Intent Completeness

Each page must fully satisfy the intent behind its pattern:

Informational
Comparative
Local
Transactional

Partial answers at scale are high risk.

5. Quality at Scale

Scaling pages does not lower the bar for quality.

100 excellent pages > 10,000 weak ones.

6. Penalty & Suppression Avoidance

Avoid:

Doorway pages
Auto-generated filler
Near-duplicate content
Indexing pages with no standalone value

The 12 Programmatic SEO Playbooks

(Strategic patterns, not guaranteed wins)

Templates
Curation
Conversions
Comparisons
Examples
Locations
Personas
Integrations
Glossary
Translations
Directories
Profiles

Only use playbooks supported by data + intent + feasibility score.

Phase 2: Page System Design

1. Keyword Pattern Definition

Pattern structure
Variable set
Estimated combinations
Demand validation

2. Data Model

Required fields
Data sources
Update frequency
Missing-data handling

3. Template Specification

Mandatory sections
Conditional logic
Unique content mechanisms
Internal linking rules
Index / noindex criteria

Phase 3: Indexation & Scale Control

Indexation Rules

Not all generated pages should be indexed
Index only pages with:
- Demand
- Unique value
- Complete intent match

Crawl Management

Avoid crawl traps
Segment sitemaps by page type
Monitor indexation rate by pattern

Quality Gates (Mandatory)

Pre-Index Checklist

Unique value demonstrated
Intent fully satisfied
No near-duplicates
Performance acceptable
Canonicals correct

Kill Switch Criteria

If triggered, halt indexing or roll back:

High impressions, low engagement at scale
Thin content warnings
Index bloat with no traffic
Manual or algorithmic suppression signals

Output Format (Required)

Programmatic SEO Strategy

Feasibility Index

Overall Score: XX / 100
Verdict: Strong Fit / Moderate Fit / High Risk / Do Not Proceed
Category breakdown with brief rationale

Opportunity Summary

Keyword pattern
Estimated scale
Competition overview

Page System Design

URL pattern
Data requirements
Template outline
Indexation rules

Risks & Mitigations

Thin content risk
Data quality risk
Crawl/indexation risk

Related Skills

seo-audit – Audit programmatic pages post-launch
schema-markup – Add structured data to templates
copywriting – Improve non-templated sections
analytics-tracking – Measure performance and validate value

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

FAQ

What does programmatic-seo do?

Design and evaluate programmatic SEO strategies for creating SEO-driven pages at scale using templates and structured data.

When should I use programmatic-seo?

Use it when you need a repeatable workflow that produces text response.

What does programmatic-seo output?

In the evaluated run it produced text response.

How do I install or invoke programmatic-seo?

Ask the agent to use this skill when the task matches its documented workflow.

Which agents does programmatic-seo support?

Agent support is inferred from the source, but not explicitly declared.

What tools, channels, or permissions does programmatic-seo need?

It uses no extra tools; channels commonly include text; permissions include no explicit permission scopes.

Is programmatic-seo safe to install?

Static analysis marked this skill as low risk; review side effects and permissions before enabling it.

How is programmatic-seo different from an MCP or plugin?

A skill packages instructions and workflow conventions; tools, MCP servers, and plugins are dependencies the skill may call during execution.

Does programmatic-seo outperform not using a skill?

About programmatic-seo

When to use programmatic-seo

You need to decide if a large-scale template-driven SEO initiative is worth pursuing. You want a framework for scoring programmatic SEO feasibility before generating pages. You need a page system and indexation strategy that avoids thin content and doorway-page risks.

When programmatic-seo is not the right choice

You need actual implementation of pages, templates, or code generation rather than strategy. You are looking for a general SEO audit unrelated to scalable template-based page creation.

What it produces

Produces text response.