This prompt is built for Stage 1: Diagnose Segment and Offer Fit and focuses on generator-grade decisions instead of generic brainstorming. It is tuned for reply, offer outcomes and returns structured outputs with explicit sequencing, constraints, and measurable checkpoints aligned to Use Cold DM Opener Library to drive execution.. Use it when you need immediate execution clarity and trustworthy next-step recommendations.
Use when you are running outreach workflow and need a high-confidence generator output for stage 1: diagnose segment and offer fit with practical detail across reply and offer.
| Variable | Description |
|---|---|
{{persona}} | Who you are messaging |
{{offer}} | What you can help with |
{{credibility}} | Proof you can mention |
Variable Inputs
Enter values, then click Apply Values.
Who you are messaging
What you can help with
Proof you can mention
All variables have values and are ready to apply.
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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 Segment and Offer Fit and produce a decision-ready deliverable that can be executed this week for Cold DM Opener Library. Primary domain signals: reply, offer. Inputs: - persona: {{persona}} - offer: {{offer}} - credibility: {{credibility}} 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 Cold DM Opener Library 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 reply options from {{persona}} tailored to {{offer}}. 2) Score each option by stage fit, credibility, and conversion alignment to {{credibility}}. 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. <!-- ThreadTrak Prompt Library · prompt: f0349df6-1289-4f7a-84ba-4361a7473e13 · do not redistribute -->
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Stage 1: Diagnose Segment and Offer Fit Candidate Variants