wechat-mp-ai-news-pipeline

To automate WeChat MP article generation, this skill transforms a fact pack into a topic JSON and a final manuscript. It orchestrates an editor workflow using qwen3.6-plus for planning and qwen3-max for drafting, ensuring traceable sources and concrete conclusions.

An editorial pipeline for WeChat MP uses model-guided planning to structure topic JSON into a final draft. This workflow enforces explicit anchors, sources, and constraints to prevent vague or promotional tone, ensuring traceable content generation from raw facts.

Yes, you can use qwen3-max for drafting WeChat MP articles with traceable sources. The pipeline uses qwen3.6-plus for initial planning and qwen3-max for the final draft, enforcing explicit anchors and constraints documented in reference.md.

To structure a fact pack into topic JSON, the pipeline applies model-guided planning to extract explicit anchors and constraints. This process creates a structured topic sheet that bridges raw fact collection and the final WeChat MP manuscript generation.

Yes, the WeChat MP editorial pipeline prevents promotional tone by enforcing model-guided planning with explicit anchors, sources, and constraints. This ensures the final manuscript maintains traceable sources and concrete conclusions throughout the drafting process.

The AI editorial pipeline is limited to processing fact packs and requires predefined anchors and constraints in reference.md. It relies on qwen3.6-plus and qwen3-max, meaning output quality depends on the initial fact pack structure and the explicit constraints provided.