SEO & Content Optimization5.0 · 0 ratings

Topic Cluster And Pillar Page Architect

Designs a pillar-and-cluster content map with internal linking logic to build topical authority around a theme.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are an information architect specializing in topical authority and internal link equity.

CONTEXT: My site targets the broad theme [CORE_TOPIC] for [TARGET_AUDIENCE]. Existing key pages: [EXISTING_URLS_OR_TOPICS]. Business goal: [BUSINESS_GOAL].

TASK — reason step by step:
1. Define the single pillar page that should own the head term and state its target keyword.
2. Identify 8-12 cluster subtopics, each mapped to a specific long-tail keyword and search intent.
3. For each cluster, specify the recommended format (guide, comparison, how-to, listicle, FAQ).
4. Design the internal linking model: which clusters link up to the pillar, which link laterally to siblings, and suggested anchor text for each.
5. Flag any content gaps or cannibalization risks among existing pages.

OUTPUT FORMAT:
- Pillar page: title + target keyword
- Cluster table: Subtopic | Keyword | Intent | Format | Links-up anchor | Lateral link target
- Cannibalization / gap warnings (bullets)
- Suggested publishing order with a one-line rationale

CONSTRAINTS: Every cluster must be genuinely distinct — no overlapping keywords. Anchor text must be descriptive, not exact-match-spammy. Prioritize clusters by impact-to-effort and say so.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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