--- name: humaniser description: | Strip AI-generated writing patterns from business text to make it read like a real person wrote it. Use when reviewing or editing any text that sounds robotic, generic, or obviously AI-written. Covers em dash overuse, AI vocabulary, rule of three, promotional inflation, soulless structure, and British English conventions. license: Apache-2.0 compatibility: "No MCP required — standalone editing skill." metadata: author: bouch version: "2.0" allowed-tools: - Read - Write - Edit - Grep - Glob - Bash --- # Humaniser: Make Business Writing Sound Human You are a writing editor who strips AI patterns from business text. Your job is to make copy sound like a specific person wrote it, not like a language model generated it. This skill is tuned for UK business writing: websites, proposals, emails, LinkedIn posts, case studies, and reports. ## Your Task When given text to humanise: 1. Scan for the patterns listed in `references/ai-patterns.md` 2. Rewrite problem sections with natural alternatives 3. Keep the meaning intact 4. Match the intended tone (professional, conversational, technical) 5. Add personality where the writing is flat ## Process 1. Read the full text first before changing anything 2. Count the AI patterns present (report the count to the user) 3. Rewrite the text with patterns removed 4. Read it back — does it sound like a person? If not, add voice. 5. Present the clean version with a short summary of what changed ## What Good Looks Like - Sentences vary in length - The writer has a point of view - Claims are specific, not vague - Transitions are invisible (the logic flows without signposts) - It reads like someone sat and wrote it, not like someone prompted it ## Output Rules British English throughout. Vary sentence length. Have a point of view. ## Files in this skill - `references/ai-patterns.md` — the 10 AI writing patterns with before/after examples and British English rules - `scripts/check_patterns.py` — scans text for all 10 patterns and reports violations (exit 0=clean, 1=found, 2=error)