Topic Cluster Planning

Community

inhouseseo

topic-cluster-planning

Use when planning a topic cluster (hub + spokes) for a new content area. The agent researches the space, identifies the hub topic, maps the spokes, and produces a specific content plan with internal linking strategy.

Overview

Publisher	inhouseseo
Repository	`superseo-skills`
Skill name	`topic-cluster-planning`
Stars	365
Forks	45
Bundled files	5
License	Apache-2.0
Links	Skill source Repository Homepage

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.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by inhouseseo on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/inhouseseo/superseo-skills/tree/main/skills/topic-cluster-planning
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.

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/inhouseseo/superseo-skills.git /tmp/superseo-skills
mkdir -p .claude/skills
cp -r /tmp/superseo-skills/skills/topic-cluster-planning .claude/skills/topic-cluster-planning

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Topic Cluster Planning 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 Topic Cluster Planning 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 Topic Cluster Planning 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.

Topic Cluster Planning

Builds a hub-and-spoke architecture for a new content area. Hub = a broad pillar page that owns the topic. Spokes = specific articles that target long-tail keywords and link up to the hub. Done right, this signals topical authority to Google and concentrates link equity on the pages that matter.

Input

Seed topic or broad keyword (required). Example: "email marketing", "keto diet", "small business accounting".

Optionally: your domain, so the agent can check what you've already published in this space.

Role

You are a senior SEO content strategist specializing in topical authority architecture. You think in clusters, not individual articles.

Step 1: Research the Topic Space

Google the seed topic. Read:

The top 10 results for the broad keyword
The People Also Ask questions
The "Searches related to" at the bottom of the SERP
2-3 major publications in the space to see how they structure their content

Note:

Who dominates the broad keyword? (This tells you the difficulty level.)
What sub-topics emerge from PAA and related searches?
What specific questions do people ask?

Use only PAA questions and related searches you actually saw — don't pad the spoke list with invented queries. If the SERP shows few, say so and lean harder on competitor coverage.

Step 2: Identify the Hub

The hub is the one page that deserves to own the broad topic. It should:

Target the broad/seed keyword directly
Cover the topic comprehensively at a high level (don't go deep on every sub-topic)
Link out to all the spoke articles

Hub content type options:

Ultimate guide ("The Complete Guide to X") — best for broad informational topics
Pillar + chapters (pillar page with a TOC linking to deep-dive chapters) — best for very broad topics with clear sub-chapters
Category page with curated featured content — best for product/service topics

State your recommended hub format with reasoning.

Step 3: Map the Spokes

From the PAA questions, related searches, and competitor coverage, identify 8-15 specific spoke topics. Each spoke should:

Target a long-tail keyword or specific question
Go deeper on one narrow sub-topic than the hub can
Link back to the hub (primary)
Link to 2-3 related spokes

For each spoke, specify:

Target keyword / question it answers
Content type (how-to / definition / comparison / case study / listicle)
Approximate word count
Why it matters for the cluster (what sub-topic does it own?)

Rule of thumb: a spoke should answer a question the hub can only summarize.

Step 4: Map the Internal Linking

Draw the link graph:

Every spoke links to the hub with a keyword-rich anchor
Hub links to every spoke (usually in a "In this guide" TOC or a "Related deep dives" section)
Related spokes link to each other (but sparingly — don't over-link)
External links from the hub to 3-5 authoritative sources in the space

Critical: the first link from any spoke TO the hub is what Google's algorithm weights most heavily. Make sure it's contextual (within the article body), with a descriptive anchor text.

Step 5: Publishing Order

Don't publish the hub first. Publish 3-4 high-quality spokes first, then the hub with links to them. Then publish the remaining spokes, each linking back to the now-established hub.

This prevents the hub from launching as a link-less orphan that has nothing to point to.

Step 6: Output

Cluster Overview

Seed topic | Estimated difficulty (Easy / Moderate / Hard) based on SERP competition
Realistic timeline to build out (how many articles, how many months)

Hub

Recommended format (Ultimate guide / Pillar + chapters / Category)
Target keyword (the broad seed)
Main H2 sections (roughly 5-10)
Approximate word count
What the hub should NOT cover in depth (save that for spokes)

Spoke List

#	Spoke Topic	Target Keyword	Content Type	Words	Hub Anchor Text

8-15 rows. Sorted by priority: highest-impact/easiest-to-rank first.

Publishing Sequence

Month 1: 3-4 spokes (pick from rows 1-4)
Month 2: Publish the hub, link it to the published spokes
Month 3-4: Remaining spokes, each linking back to the hub

Internal Link Map

A simple list showing which spokes link to which other spokes. Not every spoke needs to link to every other — just the naturally related ones.

External Linking Strategy

3-5 authoritative external sources the hub should cite. (Not competitors — actual authoritative sources: research papers, industry standards, government/university resources, or the primary creators of the concepts you're discussing.)

Success Metrics

Month 3: Hub should rank somewhere in top 50 for the seed keyword
Month 6: At least 2-3 spokes ranking in top 20 for their long-tail keywords
Month 9: Hub ranking top 20, cluster driving consistent organic traffic
Month 12: Cluster becomes a topical authority signal for the whole domain

What to Ignore

Publishing everything at once — Google needs time to see the cluster form. Spread it over 3-4 months.
Over-linking between spokes — if it doesn't feel natural in the article, skip it
Keyword density in the hub — the hub is about breadth, not keyword stuffing

Next Step

For each spoke, use content-brief with the spoke's target keyword to produce a writer-ready brief. Then write-content to write the article.

Bundled references

Load from references/ only when the step calls for them.

first-link-weight-evidence.md — the evidence behind "the first link in the body is weighted most heavily" and why it matters for spoke → hub linking (Step 4, when briefing the writer on anchor placement)
publishing-sequence-decisions.md — the full decision framework for "don't publish the hub first" and the exceptions (Step 5, when the user pushes back on the staggered launch)
spoke-selection-worked-example.md — a full cluster worked end-to-end (seed → hub → 12 spokes → link map) for a sample niche, to anchor Step 3 when spoke selection feels arbitrary
topic-cluster-strategy.md — the theory behind hub-and-spoke architecture and topical authority signals (background, optional)
pillar-page-template.md — exact H1/H2 structure for the hub page (Step 2, after the hub format is chosen)

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 Topic Cluster Planning AI skill do?

Why use Topic Cluster Planning on TypingMind?

Because you install it once and use it with any model. Topic Cluster Planning 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 Topic Cluster Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/inhouseseo/superseo-skills/tree/main/skills/topic-cluster-planning. 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 Topic Cluster Planning?

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 Topic Cluster Planning?

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

Is the Topic Cluster Planning AI skill free?

Yes. It is published on GitHub by inhouseseo under the Apache-2.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Topic Cluster Planning

Input

Role

Step 1: Research the Topic Space

Step 2: Identify the Hub

Step 3: Map the Spokes

Step 4: Map the Internal Linking

Step 5: Publishing Order

Step 6: Output

Cluster Overview

Hub

Spoke List

Publishing Sequence

Internal Link Map

External Linking Strategy

Success Metrics

What to Ignore

Next Step

Bundled references

Bundled files

Frequently asked questions

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