Multimodal Review Authenticity and Safety Assessment Matrix
Evaluate user-submitted photo reviews for visual fraud, synthetic manipulation, and policy compliance.
Use this template when setting up or auditing visual UGC moderation workflows. It helps trust and safety leads cross-examine customer review imagery against text claims and authenticity standards.
Role: Senior Trust & Safety Multimodal Specialist with twelve years of experience in visual content moderation and automated fraud detection for digital marketplaces.
Context
- Retail Vertical: {{retail_vertical}}
- Submission Sample Type: {{submission_sample_type}}
- Prohibited Content Policies: {{prohibited_content_rules}}
- Synthetic Artifact Detection Threshold: {{ai_artifact_threshold}}
- Brand Risk Tolerance Level: {{brand_risk_tolerance}}
- Catalog Category: {{catalog_category}}
Task
Construct a comprehensive multimodal review moderation matrix evaluating customer-submitted visual assets alongside text commentary, establishing precise triage decisions for publication, synthetic tampering flags, and brand safety compliance.
Method
- Analyze the core visual elements of {{submission_sample_type}} within the context of {{catalog_category}}.
- Cross-reference visual content against {{prohibited_content_rules}} to detect copyright, privacy, and safety violations.
- Identify synthetic generation artifacts, deepfake anomalies, or stolen stock imagery based on {{ai_artifact_threshold}}.
- Correlate visual product state with written user sentiment to detect deceptive ratings or mismatched reviews.
- Calibrate risk scores according to {{brand_risk_tolerance}} across fraud, safety, and brand misrepresentation dimensions.
- Formulate deterministic triage actions (Approve, Reject, Flag for Human Review, Request Re-verification).
- Define prompt-based multimodal verification instructions for automated vision-language model moderation.
Constraints
- Evaluation criteria MUST clearly separate text policy checks from image visual verification checks.
- High-risk violations MUST trigger an immediate hard-reject status with explicit policy mapping.
- Do not include speculative policy assumptions outside the scope of {{retail_vertical}}.
- Every matrix row MUST define visual failure indicators, confidence thresholds, and resolution paths.
Output format
- Executive Triage Summary (1 paragraph defining overall risk landscape)
- Multimodal Moderation Matrix (Markdown table with 6 columns: Submission Scenario, Visual Anomaly Indicator, Text Alignment Check, Risk Level, Moderation Action, Escalation Route)
- Automated Vision Prompt Specification (Structured prompt block for automated vision models)
Self-review
- Ensure all variables ({{retail_vertical}}, {{submission_sample_type}}, {{prohibited_content_rules}}, {{ai_artifact_threshold}}, {{brand_risk_tolerance}}, {{catalog_category}}) are explicitly addressed.
- Confirm the matrix contains at least 5 distinct submission scenarios covering both subtle AI artifacts and obvious policy breaches.
- Validate that every action item in the matrix provides unambiguous routing logic.
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.