Automate DTC creative production and testing with a 5-layer prompt system.
npx skills add https://github.com/afadtc/afa-dtc-skills --skill afa-creative
Please help me install this Agent Skill. Skill: afa-creative Source: https://github.com/afadtc/afa-dtc-skills/tree/main/afa-creative Command: npx skills add https://github.com/afadtc/afa-dtc-skills --skill afa-creative
Automates end-to-end creative production, testing, and iteration for DTC advertising campaigns, reducing cycle times and enabling data-driven decisions.
Generate a complete Ad Matrix for a new product using the current Brand Kit and references.
High-intent search queries and answers about installing and using this skill.
Automate DTC ad creative production by using a 5-layer prompt system to generate visuals, copy, and scripts at scale. This pipeline aligns outputs to your Brand Kit and supports cross-platform testing across Meta, TikTok, Google, and LinkedIn.
A structured testing framework for DTC advertising builds a 4x3 ad matrix to test multiple creative variants simultaneously. It tracks Tracking IDs and outputs ICE-prioritized recommendations to guide data-driven iteration and optimize performance.
Yes, you can generate UGC, bold typography, and Product Hero formats using AI-powered prompts. The system supports multi-format asset generation aligned to your Brand Kit for comprehensive campaign testing.
Scale DTC creative testing while maintaining brand consistency through Brand Kit integration. The system applies a 5-layer prompt structure and risk controls to ensure all generated visuals, matrices, and scripts adhere to predefined brand guidelines.
Yes, DTC creative testing works with Meta, TikTok, Google, and LinkedIn simultaneously. The system generates cross-platform templates and tracks performance using structured matrices to identify winning variants across all channels.
Prevent creative fatigue in DTC advertising by implementing evidence-based iteration with diagnostic checks. The system monitors performance fatigue and uses Tracking IDs to output ICE-prioritized recommendations for continuous creative optimization.
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