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Programmatic Seo

CommunityPopular
fcakyon
programmatic-seo

Use when planning many similar pages from a template and a data set: choosing the pattern, deciding whether the data can carry it, and avoiding the thin-content failure that gets page sets deindexed.

Overview

Publisherfcakyon
Repositoryclaude-codex-settings
Skill nameprogrammatic-seo
Stars
1.2K
Forks
113
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by fcakyon on GitHub. Read the source before you install it.

Installation

Install the Programmatic Seo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/fcakyon/claude-codex-settings/tree/main/plugins/seo-skills/skills/programmatic-seo
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fcakyon/claude-codex-settings.git /tmp/claude-codex-settings
mkdir -p .claude/skills
cp -r /tmp/claude-codex-settings/plugins/seo-skills/skills/programmatic-seo .claude/skills/programmatic-seo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Programmatic Seo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Programmatic Seo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Programmatic Seo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Programmatic SEO

Building pages from a template and a data set works when each page answers a real query with something only your data can say. It fails the same way every time: a template with the variable swapped, published at volume, on queries nobody searches. That is the definition of a doorway page, and Google's spam policies name it.

So the question to settle before any of the mechanics is whether the data is worth a page.

Does the data carry it

Defensibility runs in this order, strongest first:

  1. Proprietary, because you generated it.
  2. Product-derived, from how your own users behave.
  3. User-generated, from your community.
  4. Licensed, where the license is exclusive.
  5. Public, which anyone can use and everyone already has.

A set built on public data competes with every other set built on the same public data, so it has to win on presentation, freshness, or aggregation instead. That is possible and it is a much harder brief. Say so rather than shipping 5,000 pages that restate a public API.

Then check demand actually exists: aggregate volume across the pattern, how it splits between head and long tail, and whether the trend is going anywhere. A pattern with 10,000 combinations and no searches for 9,000 of them is a 1,000-page opportunity.

Choosing a pattern

You haveConsider
Proprietary data setDirectory, Profiles
A product with integrationsIntegrations
A design or creative productTemplates, Examples
Several distinct audience segmentsPersonas
A local footprintLocations
A utility or calculatorConversions
Deep subject expertiseGlossary, Curation
A crowded competitive fieldComparisons

references/playbooks.md covers the twelve patterns, each with its query shape, what data it needs, and how it usually fails.

Patterns layer, and layering is often where the real opportunity is: "best coworking spaces in Austin" is Curation crossed with Locations.

Making each page worth indexing

  • Every page needs something specific to it beyond the substituted variable: a number, a comparison, a list, an image, a genuine answer.
  • Write the introduction per page, or generate it from enough fields that no two read alike. A shared paragraph with one word swapped is the tell.
  • Vary structure by what the data supports. A page with three data points shouldn't use the layout built for thirty; branch the template instead of padding.
  • Give each page a unique title and meta description built from its variables, not one pattern with the variable appended.
  • Match the query's intent. A comparison query wants a comparison, not a signup page.

Structure and indexation

  • Subfolders, not subdomains, so the pages build authority on the same domain rather than splitting it.
  • Hub and spoke: a category page linking to every page in the set, each page linking back, and related pages cross-linking. Otherwise the set is orphaned and only the sitemap points at it.
  • Own sitemap for the set, or a sitemap per pattern, so indexing rates per pattern are readable.
  • Ship the strongest slice first rather than the whole set. Publish the highest-demand pages, confirm they get indexed and ranked, then expand. A set that goes out all at once gives no signal about which part worked.
  • Leave the thinnest variations out entirely. That is better than publishing them and noindexing them later, since crawl spent on pages you didn't want is crawl not spent on pages you did.

Before it ships

Check that each page has unique value and answers its query, that titles and descriptions are unique, that heading structure and schema are in place, that the set is linked from the site rather than only the sitemap, that no page has a conflicting noindex, and that nothing in the set competes with an existing page for the same query.

After launch, watch what fraction of the set gets indexed, which patterns rank, and whether engagement holds up. Thin-content warnings, a drop across the set, or an indexing rate that stalls well below 100% all mean the same thing: cut, don't add.

What this hands off

Programmatic SEO decides the pattern, the data, the URL shape, the template's sections, and the linking. The words inside a template section are copy: hand the content marketer the template, the target query, and the fields available per page.

Sources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Programmatic Seo AI skill do?

Use when planning many similar pages from a template and a data set: choosing the pattern, deciding whether the data can carry it, and avoiding the thin-content failure that gets page sets deindexed.

Why use Programmatic Seo on TypingMind?

Because you install it once and use it with any model. Programmatic Seo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Programmatic Seo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fcakyon/claude-codex-settings/tree/main/plugins/seo-skills/skills/programmatic-seo. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Programmatic Seo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Programmatic Seo?

As many as you like. As long as a model supports skills, you can use Programmatic Seo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Programmatic Seo AI skill free?

Yes. It is published on GitHub by fcakyon under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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