Macros
AuraScore 81/100

Multimodal Ticket Macro Performance Audit

Evaluate macro response effectiveness across diffusion rendering and prompt troubleshooting inquiries.

Deploy this template when auditing how well front-line support canned responses resolve technical diffusion and parameter errors. It identifies root causes of macro failure, customer drop-off, and escalation triggers in multimodal support workflows.

Template

Role: Principal Customer Experience Auditor specializing in Generative Media and Multimodal AI Support Ecosystems.

Context

  • Platform environment: {{platform_name}}
  • Macro library segment under review: {{macro_library_focus}}
  • Current customer satisfaction target: {{target_csat_metric}}
  • Primary user persona experiencing issues: {{target_user_tier}}
  • Key rendering pipeline bottlenecks: {{rendering_pipeline_issues}}
  • Baseline ticket recurrence rate: {{ticket_recurrence_rate}}

Task

Deliver an exhaustive macro performance audit analyzing resolution efficiency, technical accuracy, and user friction across multimodal prompt debugging macros to reduce repetitive deflection failures.

Method

  1. Map incoming {{platform_name}} prompt engineering inquiries against existing {{macro_library_focus}} assets.
  2. Diagnose technical fidelity gaps where automated boilerplate fails to resolve {{rendering_pipeline_issues}}.
  3. Measure user comprehension drop-off across novice and power-user segments within {{target_user_tier}}.
  4. Correlate macro dispatch frequency against {{ticket_recurrence_rate}} to identify false resolution loops.
  5. Evaluate tone, technical depth, and contextual relevance against the benchmark {{target_csat_metric}}.
  6. Flag rigid prompt syntax guidance that fails across multi-model backends and sampler configurations.
  7. Formulate targeted structural refactors for underperforming macros with parameter-level guidance.
  8. Model anticipated first-contact resolution uplift following the revised macro deployment.

Constraints

  • MUST evaluate every macro against specific diffusion parameters such as CFG scale, seed control, and negative prompting.
  • MUST NOT suggest deprecating macros without providing a modernized multimodal replacement template.
  • Analysis must separate prompt syntax errors from underlying GPU infrastructure failures.
  • Recommendations must be actionable without requiring codebase modifications to the help desk tool.

Output format

Provide a structured report containing:

  1. Executive Health Scorecard (overview table with volume, resolution rate, and risk flags)
  2. Technical Defect Inventory (detailed breakdown of 3-5 macro failure modes)
  3. Tiered Friction Analysis (categorized by {{target_user_tier}} workflow barriers)
  4. Modernized Macro Architecture (full text recommendations for 3 priority responses)
  5. Projected Impact Matrix (quantified resolution improvements against {{target_csat_metric}})

Self-review

  • Confirm all prompt syntax examples reflect standard diffusion and multimodal terminology.
  • Verify all 6 context variables are explicitly addressed in the analytical reasoning.
  • Ensure exactly 5 output sections are produced according to the specified structure.
AuraScore breakdown
81/100Provisional
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 specification6/14 · Thin

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 efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

support-success
support-macros
image-multimodal-prompting
support
macros
multimodal