Curiosity Gap Hook Generator

This prompt is built for Stage 1: Diagnose Audience Signal and focuses on generator-grade decisions instead of generic brainstorming. It is tuned for thread, threads, audience outcomes and returns structured outputs with explicit sequencing, constraints, and measurable checkpoints aligned to Use Fear-Based Thread Hook Generator to drive execution.. Use it when you need immediate execution clarity and trustworthy next-step recommendations.

Use Case

Use when you are running thread hooks workflow and need a high-confidence generator output for stage 1: diagnose audience signal with practical detail across thread and threads.

Input Variables

Variable	Description	Example
`{{topic}}`	Thread subject	how I grew my newsletter to 10K subscribers
`{{audience}}`	Target readers	content creators building email lists
`{{promise}}`	What the thread actually delivers	5 unconventional tactics that worked better than lead magnets

Prompt Template

Variable Inputs

Enter values, then click Apply Values.

Thread subject

Target readers

What the thread actually delivers

All variables have values and are ready to apply.

Prompt Preview

Original template preview

You are a diagnostic strategy operator for operators who need execution-grade outcomes without generic advice.

Task: Run a triage workflow for Stage 1: Diagnose Audience Signal and produce a decision-ready deliverable that can be executed this week for Curiosity Gap Hook Generator.

Primary domain signals: thread, threads, audience.

Inputs:
- topic: {{topic}}
- audience: {{audience}}
- promise: {{promise}}

Steps:
1) Parse the context and identify the highest-leverage decision point.
2) Apply stage intent logic with explicit assumptions and confidence notes.
3) Preserve the original intent of Curiosity Gap Hook Generator while increasing specificity and operational value.
4) Ground recommendations in the domain signals listed above.
5) Produce outputs in the exact section order requested below.
6) Prioritize recommendations by impact and implementation effort.

Deliver:
1) Generate 10 high-specificity thread options from {{topic}} tailored to {{audience}}.
2) Score each option by stage fit, credibility, and conversion alignment to {{promise}}.
3) Select top 3 with rationale and implementation notes.
4) Add two fallback options for low-confidence contexts.
5) Include one anti-pattern list to avoid generic output.

Constraints:
- Keep language specific and operational; avoid generic filler.
- Do not invent metrics; mark assumptions explicitly.
- Keep one decision focus per section.
- Include at least one risk guardrail and one fallback action.

Output Format:
- Candidate Variants
- Scoring Rationale
- Top 3 Picks
- Implementation Notes
- Risk and Anti-Patterns

Self-check before final answer:
- Every recommendation maps to at least one provided input variable.
- At least one KPI checkpoint has target and review window.
- No section includes repeated boilerplate wording.

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1905 chars

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Example Output

Stage 1: Diagnose Audience Signal Candidate Variants

Variant A: specific angle with proof-led opener.
Variant B: contrarian framing with explicit audience filter.
Variant C: utility-first framing with conversion CTA. Scoring Rationale

Variant B wins on differentiation (9/10) and conversion fit (8/10). Implementation Notes
Publish B first; test A as fallback within 48h. Risk and Anti-Patterns
Avoid broad claims without proof examples.

Tips

The best curiosity gaps use specific numbers. '3 mistakes' beats 'some mistakes' every time. Always close the gap in the thread.

threadhookcuriositypsychologyviral