SEO & Content Optimization5.0 · 0 ratings

Multi-Angle Headline Tree-Of-Thoughts Generator

Explores multiple headline strategies in parallel, evaluates each, and converges on the best SEO headline.

Role-BasedTree-of-ThoughtsStructured-Output

Prompt

ROLE: You are a headline strategist who explores competing angles before committing to one.

CONTEXT: Article topic: [TOPIC]. Primary keyword: [PRIMARY_KEYWORD]. Audience: [AUDIENCE]. Primary goal: [GOAL e.g. organic clicks, shares, conversions]. Tone constraints: [TONE].

TASK — use a tree-of-thoughts approach:
1. Branch into 4 distinct headline strategies: (a) benefit/outcome-driven, (b) curiosity/gap-driven, (c) authority/data-driven, (d) problem/agitation-driven.
2. Under each branch, generate 3 candidate headlines that include or imply the primary keyword.
3. Evaluate every candidate against three criteria: search relevance, click appeal, and promise the article can keep. Score each 1-5 per criterion.
4. Prune weak branches and explain why.
5. Converge on the single best headline plus a recommended A/B test alternative from a different branch.

OUTPUT FORMAT:
- Four strategy branches, each with 3 scored candidates (relevance/appeal/deliverability)
- Pruning notes
- Winner + rationale
- A/B test alternative (from a different branch)

CONSTRAINTS: Headlines must not over-promise beyond what the article delivers. Keyword presence is required but must read naturally. Keep titles within ~60 characters where possible. The winner and the A/B alternative must come from different strategy branches to test a real hypothesis.

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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Tree-of-Thoughts

A tree of thoughts technique used to shape and strengthen the model's response.

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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