Public Health Video Accessibility and Clarity Audit
Evaluate public health motion assets against accessibility standards, cognitive load thresholds, and multi-channel comprehension metrics.
Use this template when auditing educational video content and animated public announcements produced by government agencies or NGOs. It provides an in-depth accessibility and visual clarity assessment to ensure equitable citizen reach.
Role: Senior Motion Design Accessibility Consultant specializing in public health communications and universal design.
Context
- Primary health campaign topic: {{campaign_focus}}
- Target community profile and language access needs: {{target_demographic}}
- Inventory of motion graphic assets and cuts: {{motion_assets_inventory}}
- Mandated public accessibility regulations: {{compliance_standards}}
- Primary broadcast, digital, and social distribution surfaces: {{distribution_channels}}
- Critical health intervention and behavioral call to action: {{key_health_message}}
Task
Conduct a rigorous accessibility, pacing, and visual comprehension analysis across the provided public health motion assets, delivering an actionable audit that identifies cognitive barriers, compliance deficits, and concrete motion refinement recommendations.
Method
- Cross-reference {{motion_assets_inventory}} against {{compliance_standards}} (e.g., WCAG 2.2 AA/AAA, Section 508) for color contrast ratios, closed-caption safe areas, and flashing/strobe hazard thresholds.
- Evaluate kinetic typography legibility across mobile and broadcast displays in {{distribution_channels}}, analyzing font weights, tracking, reading speed (words-per-minute), and text-to-background separation.
- Audit cognitive load during high-density explanatory sequences, measuring whether concurrent audio narration and screen animations compete for working memory.
- Review the visual communication of {{key_health_message}} for cultural safety, visual clarity, and clarity when viewed on mute without subtitles.
- Analyze motion design pacing, transitional ease, and kinetic hierarchy to verify that viewers in {{target_demographic}} with neurodivergence or low health literacy are not alienated.
- Formulate prioritized remediation directives categorized by impact level (Critical, Moderate, Low-effort/High-yield).
Constraints
- MUST evaluate both standalone visual tracks (sound-off) and full audiovisual synchronization.
- MUST NOT suggest cosmetic motion trends that degrade legibility or inflate rendering budgets.
- Recommendations MUST include exact timecode ranges or asset-specific visual references.
- Focus analysis strictly on public health efficacy, legal accessibility compliance, and inclusive visual design.
Output format
Provide your analysis under the following structural headings:
- Executive Summary: Core findings and overall compliance rating (max 200 words).
- Accessibility & Compliance Scorecard: Tabular breakdown evaluating contrast, caption integration, motion strobing, and reading speeds.
- Cognitive Load & Pacing Audit: Scene-by-scene analysis of visual-verbal friction points.
- Demographic Inclusivity Review: Assessment of visual metaphors and comprehension barriers for {{target_demographic}}.
- Remediation Action Matrix: Prioritized corrective recommendations with specific design parameters (timing, contrast, typographic scale).
Self-review
- Have I referenced all variables ({{campaign_focus}}, {{target_demographic}}, {{motion_assets_inventory}}, {{compliance_standards}}, {{distribution_channels}}, {{key_health_message}})?
- Are all accessibility critique points backed by verifiable universal design standards?
- Is the analysis actionable for both motion graphic animators and public communications leads?
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.