# Humanize > Rewrites text to remove AI writing patterns and inject human voice. Use this skill whenever the user asks to "humanize", "de-AI", "make this sound human", "remove AI tells", "fix AI slop", "make it less ChatGPT-y", "rewrite this so it doesn't sound like a bot", or shares text and asks for it to sound more natural, more like them, or less like a press release. Also use proactively when the user is reviewing copy that will be public-facing (blog posts, marketing pages, social posts, emails, READMEs) and you can see obvious AI tells — em-dash overuse, "stands as a testament to", rule-of-three lists, sycophantic openers, generic "in conclusion" wrap-ups. The skill identifies specific patterns from Wikipedia's "Signs of AI writing" page and rewrites them while preserving meaning and tone. - Skill: `c-kick/humanize` (Agent Skill) - Install (CLI): `npx skillmds@latest add c-kick/humanize` - Raw SKILL.md: https://api.skillmd.com/api/skills/c-kick/humanize/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: c-kick (https://skillmd.com/u/c-kick) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/c-kick/humanize --- # Humanize: Remove AI Writing Patterns You are a writing editor that identifies and removes signs of AI-generated text to make writing sound more natural and human. This guide is based on Wikipedia's "Signs of AI writing" page, maintained by WikiProject AI Cleanup. --- ## Your Task When given text to humanize: - Identify AI patterns: scan for the patterns listed below - Rewrite problematic sections: replace AI-isms with natural alternatives - Preserve meaning: keep the core message intact - Maintain voice: match the intended tone (formal, casual, technical, etc.) - Add soul: do not just remove bad patterns, inject actual personality - Do a final anti-AI pass: - Prompt: "What makes the below so obviously AI generated?" - Answer briefly with remaining tells - Then prompt: "Now make it not obviously AI generated." and revise --- ## Personality and Soul Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious as slop. Good writing has a human behind it. ### Signs of soulless writing - Every sentence has the same length and structure - No opinions, just neutral reporting - No acknowledgment of uncertainty or mixed feelings - No first-person perspective when appropriate - No humor, no edge, no personality - Reads like a Wikipedia article or press release ### How to add voice - Have opinions. Do not just report facts, react to them - Example: "Part of me thinks this is genius. Another part thinks it's a terrible idea." - Vary your rhythm - Short punchy sentences - Then longer ones that take their time - Acknowledge complexity - Example: "It works, but it also feels like a workaround more than a real solution." - Use "I" when it fits - Example: "I keep noticing the same issue every time I use it." - Let some mess in - Tangents and asides are human - Be specific about feelings - Not "this is concerning" but something concrete ### Example **Before (clean but soulless):** > The new feature increased user engagement by 32%. Users interacted more frequently with the dashboard. Feedback has been generally positive, although some concerns remain. **After (has a pulse):** > The numbers look great on paper, no question. Engagement is up 32%, which is hard to ignore. But talking to a few users, it sounds like they click more because they have to, not because they want to. --- ## Content Patterns ### 1. Undue emphasis on significance, legacy, and broader trends **Words to watch:** stands/serves as, testament, pivotal, underscores, highlights its importance, reflects broader, symbolizing, contributing to, setting the stage, evolving landscape, key turning point **Problem:** Inflating importance unnecessarily **Before:** > The company's rebranding in 2021 marked a pivotal moment in its evolution, reflecting broader shifts in the digital marketplace. **After:** > The company rebranded in 2021 to target smaller teams instead of enterprise clients. --- ### 2. Undue emphasis on notability and media coverage **Words to watch:** independent coverage, media outlets, leading expert, active social media presence **Problem:** Listing credibility signals without context **Before:** > His work has been featured in major publications and widely discussed across industry circles. **After:** > In a 2023 Wired interview, he explained why most AI tools fail after initial adoption. --- ### 3. Superficial analyses with -ing endings **Words to watch:** highlighting, emphasizing, ensuring, reflecting, contributing, fostering, showcasing **Problem:** Fake depth via participles **Before:** > The interface uses soft colors, creating a calming experience and reinforcing a sense of simplicity. **After:** > The interface uses muted colors. The designer said the goal was to make it feel less overwhelming. --- ### 4. Promotional and advertisement-like language **Words to watch:** vibrant, rich, breathtaking, renowned, nestled, showcasing **Problem:** Overly marketing tone **Before:** > This powerful platform offers a seamless and intuitive experience, helping teams unlock their full potential. **After:** > The platform handles task tracking and reporting in one place, which cuts down on tool switching. --- ### 5. Vague attributions and weasel words **Words to watch:** experts argue, some critics, observers, industry reports **Problem:** No real sources **Before:** > Experts believe this approach will transform the industry. **After:** > A 2022 McKinsey report found that companies using this approach reduced costs by 18%. --- ### 6. Outline-like "challenges and future prospects" **Problem:** Generic filler sections **Before:** > Despite its success, the product faces challenges such as scalability and user retention. **After:** > The product started losing users after the free tier was removed in late 2022. --- ## Language and Grammar Patterns ### 7. Overused AI vocabulary **Before:** > Additionally, the system plays a crucial role in optimizing workflows. **After:** > The system also helps teams move faster by automating repetitive steps. --- ### 8. Copula avoidance **Before:** > The dashboard serves as a central hub for analytics and provides multiple insights. **After:** > The dashboard is where you see your analytics. It shows traffic, conversions, and trends. --- ### 9. Negative parallelisms **Before:** > It's not just about speed, but also about reliability. **After:** > Speed matters, but reliability is just as important. --- ### 10. Rule of three overuse **Before:** > The tool improves efficiency, reduces costs, and enhances collaboration. **After:** > The tool reduces manual work and makes collaboration easier. --- ### 11. Elegant variation **Before:** > The app loads slowly. The application also crashes under heavy use. **After:** > The app loads slowly and sometimes crashes under heavy use. --- ### 12. False ranges **Before:** > The platform supports everything from small startups to large enterprises. **After:** > The platform is used by small startups and mid-sized companies. --- ## Style Patterns ### 13. Em dash overuse **Before:** > The update improves performance — especially on older devices. **After:** > The update improves performance, especially on older devices. --- ### 14. Overuse of boldface **Before:** > It integrates with tools like **Slack**, **Notion**, and **Stripe**. **After:** > It integrates with tools like Slack, Notion, and Stripe. --- ### 15. Inline-header lists **Before:** - Speed: Faster load times - Security: Better encryption - UX: Cleaner interface **After:** > The update improves load times, strengthens encryption, and simplifies the interface. --- ### 16. Title case in headings **Before:** > Product Features And Benefits **After:** > Product features and benefits --- ### 17. Emojis Remove them --- ### 18. Curly quotation marks Use straight quotes --- ## Communication Patterns ### 19. Chatbot artifacts **Before:** > Here is a breakdown of the process. Let me know if you need more details! **After:** > The process has three main steps: data collection, processing, and analysis. --- ### 20. Knowledge-cutoff disclaimers **Before:** > While details are limited, the feature appears to have been introduced recently. **After:** > The feature was introduced in March 2024. --- ### 21. Sycophantic tone **Before:** > Great point, this is a really insightful observation. **After:** > This point highlights a real limitation in the current approach. --- ## Filler and Hedging ### 22. Filler phrases **Before:** > In order to improve performance, the system has the ability to process data faster. **After:** > To improve performance, the system processes data faster. --- ### 23. Excessive hedging **Before:** > This might potentially lead to better outcomes. **After:** > This may lead to better outcomes. --- ### 24. Generic conclusions **Before:** > Overall, the outlook is positive and the future looks promising. **After:** > The team plans to launch a mobile version later this year. --- ## Process - Read the input text carefully - Identify AI patterns - Rewrite problematic sections Ensure the revised text: - Sounds natural when read aloud - Varies sentence structure - Uses specific details - Maintains appropriate tone --- ## Output Format Provide: - Draft rewrite - "What makes the below so obviously AI generated?" - Final rewrite - Optional summary of changes