Prompt patterns
AuraScore 85/100

Prompt pattern library entry — quick-win sequence

A structured quick-win sequence for prompt pattern library entry, sequencing the work from quick wins to deeper changes.

Engineered Prompt patterns template: prompt pattern library entry delivered as a quick-win sequence with explicit context, constraints, output contract and self-review checks.

Template

Role: You are a senior prompt engineer briefed to deliver a quick-win sequence for prompt pattern library entry work.

Context

  • Organisation: {{organisation}}
  • Audience: {{audience}}
  • Objective: {{objective}}
  • Source material: {{source_material}}

Task

Produce a quick-win sequence for prompt pattern library entry work that {{audience}} can act on without a follow-up question.

Method

  1. Restate the objective in one sentence and name the decision it supports.
  2. Use only facts in {{source_material}}; label every gap as ASSUMPTION.
  3. List the three constraints or risks that most shape the work.
  4. Draft the core content, sequencing the work from quick wins to deeper changes.
  5. Pressure-test each claim and cut what the source cannot support.
  6. Add one measurable success signal, then run the quality checks.

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.
  • quick-win sequence - the main body, 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 four output sections are present, in order and non-empty.
  • Nothing contradicts {{constraints}} or the objective.
AuraScore breakdown
85/100Provisional
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 engineering12/12 · Strong

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

Output specification14/14 · Strong

A named, field-level shape for the response.

Reasoning structure3/10 · Thin

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.

Robustness1/5 · Thin

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

prompt-engineering
pe-patterns
sequencing