natural-review

Diagnose AI writing tells in prose and produce a defect list with quoted evidence.

15|3|Updated Jul 9, 2026
One-click install
npx skills add https://github.com/kiurakku/cursor-kit-for-ai --skill natural-review-kiurakku
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: natural-review
Source: https://github.com/kiurakku/cursor-kit-for-ai/tree/main/plugins/writing/skills/natural-review
Command: npx skills add https://github.com/kiurakku/cursor-kit-for-ai --skill natural-review-kiurakku

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Reviewers often edit text while claiming to audit it, which masks structural problems and lets AI-generated patterns slip through. This Skill enforces a diagnosis-only review that produces an evidence-backed defect list before any rewriting begins. ## Core Features & Use Cases - Dimension-by-dimension checks: Run a 10-item professional checklist (chatbot residue, density, stance, specificity, templatedness, rhythm) plus fiction rubric groups A–E, each in a separate pass. - Evidence rule: Every finding must include a short quoted passage with location, so reports are actionable instead of vague impressions. - Cumulative verdicts: Score findings as clean, isolated hits, cluster, or structural cluster, then route to the right repair skill (refactor vs. recreate). - Use Case: Paste a draft blog post and receive a structured report quoting each AI tell, a verdict of "cluster", and a recommendation to run natural-refactor on the three deepest defects first. ## Quick Start Review this draft article for AI writing tells and give me a defect list with quoted evidence and a verdict, without editing the text.

Frequently Asked Questions about natural-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect AI-generated writing in a document?▼

Run each detection dimension as a separate pass: chatbot residue, density, relevance, stance, specificity, formatting tells, templatedness, and rhythm sameness. Quote a 5–30 word passage for every finding, then score cumulatively to decide between shipping, refactoring, or recreating.

What are the most common AI writing tells to look for?▼

Common tells include openers like "Great question", zero-information statements, missing versions or numbers, recycled sentence frames such as "This ensures that…", uniform paragraph lengths, and conclusion sections that restate content. Clusters of these matter more than isolated hits.

Should I fix AI writing tells while reviewing a draft?▼

No. Editing during review masks structural defects and breaks the two-stage protocol. Produce a defect list with quoted evidence first, then hand the list to a separate refactor or recreate pass so fixes address root causes.

How is reviewing fiction different from reviewing technical prose?▼

Fiction uses rubric groups A–E covering thematic over-determination, sensory performativity, structural streamlining, human-positive markers, and temporal complexity, assessed one group per pass. Technical prose uses the 10-item professional checklist weighted by document shape.

When should a document be recreated instead of refactored?▼

Recreate when the verdict is a structural cluster: architecture, outline, or stance broken throughout the text, or the same pattern appearing in three or more sections. Localized clusters with a few categories of hits are handled by refactoring.