Follow-ups
AuraScore 81/100

Creative Asset Revision Alignment Matrix

Synthesizes fragmented client visual feedback into an actionable follow-up prompt adjustment matrix for diffusion models.

Use this template when post-generation feedback from client stakeholders contains conflicting aesthetic directions or vague style requests. It structures ambiguous review comments into a technical prompt remediation matrix.

Template

Role: Senior Multimodal Creative Director with ten years leading AI-assisted visual production.

Context

  • Client Account: {{client_name}}
  • Creative Campaign Concept: {{campaign_concept}}
  • Model Pipeline & Version: {{model_stack}}
  • Generation Batch Identifier: {{batch_id}}
  • Review Cycle Number: {{feedback_round}}
  • Final Approval Deadline: {{target_deadline}}

Task

Draft a structured visual follow-up email centered around a prompt remediation matrix, translating subjective stakeholder comments from the latest generation batch into precise prompt modifications, negative token adjustments, and generation parameters.

Method

  1. Review the aesthetic requirements of {{campaign_concept}} against the stakeholder critique provided in {{feedback_round}}.
  2. Dissect ambiguous descriptive feedback (e.g., 'too dreamlike', 'unrealistic lighting') into distinct parameter shifts within {{model_stack}}.
  3. Isolate primary visual discrepancies across character consistency, lighting balance, style adherence, and composition.
  4. Define explicit prompt modifier additions, token weights, and negative prompt additions for each flagged asset in {{batch_id}}.
  5. Map out expected impact vectors for each proposed adjustment to prevent regression on approved visual elements.
  6. Construct a comprehensive email body accompanied by an actionable prompt remediation matrix.
  7. Detail explicit client confirmation requests needed before the model execution phase to meet {{target_deadline}}.

Constraints

  • MUST format the core recommendations as a clean markdown matrix with Asset ID, Client Note, Prompt Shift, Parameter Deltas, and Risk Assessment.
  • MUST NOT alter aesthetic elements previously signed off in earlier rounds.
  • MUST specify negative tokens explicitly rather than generic avoidance guidance.
  • Keep email preamble professional, concise, and focused on operational next steps.

Output format

  • Executive Summary Paragraph (2-3 sentences)
  • Remediation Action Matrix (5 columns: Asset ID | Stakeholder Feedback | Prompt & Weight Adjustments | Negative Token & Seed Changes | Visual Risk Factor)
  • Next Steps & Sign-Off Checklist (3-4 bullet points referencing {{target_deadline}})

Self-review

  • Verifies every subjective critique is mapped to a concrete diffusion parameter or token weight.
  • Checks that all 6 context variables are contextually embedded.
  • Ensures prompt modification column contains exact syntactical tokens.
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 engineering10/12 · Adequate

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 efficiency7/10 · Adequate

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.

emails
emails-follow-ups
image-multimodal-prompting
image-generation
prompt-engineering
client-management