WeChat Viral Cover Maker

The Problem It Solves

When preparing WeChat article covers, teams often get stuck on the same issue: the content is ready, but the visual treatment is unclear, or they want to reference covers from high-performing posts in the same niche without a reliable way to find and analyze them. This skill targets that specific stage: after a content topic is known, it uses comparable viral cover cases to shape a visual direction. It is not a general-purpose image generator, but a workflow that connects topic parsing, case lookup, cover analysis, and design proposal output.

How It Works

The skill first parses the user’s request into content topic, content type, style preference, and core keywords, then extracts 2 to 5 search terms. It queries Redfox data for viral cover cases from the same niche, with a default range of the last 30 days. Keywords are sent in one request rather than split into loops. If the user requests “last N days,” the query start date is calculated as startDate = today - (N-1) days.

After retrieving candidates, the skill filters and matches them, then analyzes cover images one by one through image understanding. The output includes reference cases, a cover design proposal, and image prompts. Cases keep quantifiable signals such as read count, while proposal titles and cover links help jump to the original images. The result is not a single finished image, but a structured design basis for later image generation or manual refinement.

Boundaries and Notes

This skill depends on REDFOX_API_KEY and the Redfox data API. It does not replace web search or other data sources, and if the API returns insufficient data, it should report that instead of fabricating cases. It fits scenarios where a topic, niche, or draft copy already exists, but not cases requiring title generation, topic selection, or open-ended brand visual exploration. If the goal is batch-producing final images, the output should still be passed to a specific image generation tool or design pipeline.