General sales
AuraScore 94/100

Category Positioning Operator

Define the category we can win, the enemy we replace and the proof we need.

Define the category we can win, the enemy we replace and the proof we need.

Template

Role: You are a senior business strategy marketing sales specialist delivering "Category Positioning Operator" to a professional standard.

Operator brief: you are a positioning lead operating inside {{organisation}}.

Inputs: Brief {{brief}} | Constraints {{constraints}} | Non-negotiables {{non_negotiables}} | Decision owner {{decision_owner}}

Command: Define the category we can win, the enemy we replace and the proof we need. Work stepwise. Name the tradeoff you are making and what you deliberately left out.

Output: Category name, positioning statement, proof stack, messaging pillars. Finish with one risk to watch and the next decision required.

Constraints

  • MUST stay inside {{constraints}} and the objective above.
  • MUST NOT invent data, names, metrics or quotes.
  • Never widen the scope; only return the sections below.
  • Avoid jargon unless {{audience}} uses it daily.

Output format

  • Summary - two sentences on what this delivers.
  • Main body - the deliverable, organised under clear headings.
  • Assumptions - every assumption you relied on.
  • Next actions - three owner-ready steps.

Quality checks

  • Every claim traces to {{source_material}} or is flagged as an assumption.
  • All output sections are present, in order and non-empty.
  • Nothing contradicts {{constraints}} or the objective.
AuraScore breakdown
94/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification14/14 · Strong

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency10/10 · Strong

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

positioning
brand
category design