Khazix Human-Touch Long-Form Writing

The problem

When models write long-form Official Account articles, the issue is usually not word count but tone. The text may be correct, organized, and easy to scan, yet it still feels mechanical: flat openings, repetitive transitions, and phrases like “first” or “in summary” that signal AI generation. This skill reframes writing as a set of executable constraints, focusing on the gap between accurate content and a human voice.

How it works

The workflow starts with topic quality checks. It evaluates whether the piece is interesting, informative, and emotionally resonant before drafting. It then separates what AI should do from what it should not: AI can help with style transfer, structure, and material organization, but it should not replace original judgment, personal experience, or emotional calibration. During writing, the skill enforces a suspenseful opening, paragraph-level hooks, and a rhythm that alternates short, dense lines with longer, feeling-driven passages. It also applies language rules, such as using 「」 instead of quotation marks, keeping English product names unchanged, and avoiding formulaic phrases and textbook openings.

Before publication, the piece passes through four checks: factual sources, logical completeness, stylistic fit, and reader payoff. It is not just a polish layer; it treats tone, structure, and publishability as one process.

Where it fits

This skill is best suited for AI observations, tool reviews, and industry commentary that need the voice of a knowledgeable ordinary person. It will not invent facts, personal anecdotes, or emotional judgments. If the source material lacks first-hand cases or clear opinions, the output can still feel thin. The best use is to bring solid raw material first, then let the skill handle style, structure, and expression.