lunheng-article-pipeline-dsh

The process of creating deep articles or papers often presents challenges: how to ensure comprehensiveness, depth, and originality? Traditional single AI generation may lack multi-angle verification and systematic workflows. The Lunheng plugin addresses this by leveraging the DeepSeek Harness framework to break down article production into nine specialized role cards, forming a complete multi-agent pipeline from literature retrieval and data analysis to critical review.

Its core strength lies in structured collaboration: three retrieval agents (T1-T3) work in parallel to ensure broad information coverage; writing and analysis roles (T4-T6) process content deeply, with T6 as a critique partner specifically attacking arguments from opposing sides to enhance robustness; audit roles (T7, G0-G14) independently check quality, including Chinese AI trace detection; and final delivery is secured through a mechanical end-check (M-Gate) with evidence-based results. This design not only mimics real team collaboration but also ensures traceable verification at every step.

This plugin is ideal for users requiring high-quality deep content, such as academic researchers, professional authors, think tank analysts, or content strategists. Whether you are writing papers, reports, or long-form articles, it offers an automated pipeline from draft to final product, especially suitable for scenarios demanding rigor and innovation. With flexible model configuration—from zero-config single-model to multi-model tiering—users can balance cost and performance based on their needs, getting started easily.