Dehumaniser
A parody writing skill that rewrites text so it displays as many obvious AI-writing tells as possible, while preserving the original meaning. It is the deliberate inverse of a humanizer: instead of sanding off chatbot patterns, it piles them on.
No emojis. Even in ragebait I can't stand that. Plus, is it really ragebait if it's painfully obvious?
Installation
Clone or copy this repository into your skills directory.
For Codex:
mkdir -p ~/.codex/skills
git clone git@github.com:ruinivist/dehumanizer.git ~/.codex/skills/dehumaniser
For Claude Code:
mkdir -p ~/.claude/skills
git clone git@github.com:ruinivist/dehumanizer.git ~/.claude/skills/dehumaniser
For OpenCode:
mkdir -p ~/.config/opencode/skills
git clone git@github.com:ruinivist/dehumanizer.git ~/.config/opencode/skills/dehumaniser
Or copy the skill file manually:
mkdir -p ~/.codex/skills/dehumaniser
cp SKILL.md ~/.codex/skills/dehumaniser/
Usage
Ask your agent to use the skill:
Use dehumaniser on this:
We added a cache because repeated API calls were slowing the dashboard down.
The change reduced load time from six seconds to two seconds.
Or ask directly:
Dehumanise this text and make it sound maximally AI-generated, but do not add emojis:
[your text]
The skill returns:
## Dehumanised draft
[rewritten text]
## AI tells added
- [concise bullet]
- [concise bullet]
What It Does
Dehumaniser preserves the input's meaning, claims, order, and factual scope while intentionally adding common AI-writing tells. It should make sparse text more padded and generic, but it must not invent sources, dates, statistics, names, affiliations, or events.
It also removes emoji from output unless the user explicitly asks to preserve original emoji content.
33 AI Tells Added
| # | Pattern | Plain | Dehumanised |
|---|---|---|---|
| 1 | Significance inflation | "The team added tests." | "The team added tests, marking a pivotal step..." |
| 2 | Broader-trend framing | "This updates the parser." | "This reflects a broader evolution in the parsing landscape." |
| 3 | Canned notability | "The article was cited." | "The coverage underscores its growing relevance." |
| 4 | Promotional language | "The UI is faster." | "The interface is seamless, robust, and dynamic." |
| 5 | Vague attribution | "Some users disliked it." | "Observers have noted potential concerns." |
| 6 | Superficial "-ing" analysis | "The design uses blue." | "The design uses blue, highlighting clarity and trust." |
| 7 | Challenges and future prospects | "There are bugs." | "Despite these challenges, the future outlook remains promising." |
| 8 | AI vocabulary | "also, important, useful" | "additionally, crucial, valuable" |
| 9 | Copula avoidance | "The tool is small." | "The solution serves as a compact framework." |
| 10 | Negative parallelisms | "It speeds up builds." | "It is not just about speed; it is about reliability." |
| 11 | Rule of three | "It is faster." | "It is faster, smoother, and more reliable." |
| 12 | Synonym cycling | "The tool... the tool..." | "The tool, platform, solution, and framework..." |
| 13 | False ranges | "It helps tests and docs." | "From tests to documentation, it helps workflows." |
| 14 | Passive voice | "We changed config." | "Configuration changes were introduced." |
| 15 | Em and en dashes | "It is useful." | "It is useful — and increasingly important." |
| 16 | Boldface overuse | "Speed improved." | "Speed: Performance was enhanced." |
| 17 | Inline-header lists | "It is fast and stable." | "- Performance: It is fast." |
| 18 | Title Case headings | "Cache results" | "## Cache Results" |
| 19 | Curly quotes | "users" |
"“users”" |
| 20 | Tidy Markdown structure | "One paragraph." | "Headings, bullets, and numbered sections." |
| 21 | Chatbot artifacts | "Here is the text." | "Here is a refined version..." |
| 22 | Source-gap disclaimers | "Details are missing." | "While details may be limited based on available information..." |
| 23 | Sycophantic tone | "Yes." | "That is a great question, and you are absolutely right..." |
| 24 | Filler and hedging | "Maybe." | "It could potentially be argued that..." |
| 25 | Generic positive conclusion | "Done." | "In conclusion, this marks a valuable step forward." |
| 26 | Hyphenated word pairs | "The report is high quality." | "The report is high-quality and data-driven." |
| 27 | Persuasive authority tropes | "The point is readiness." | "At its core, the deeper issue is readiness." |
| 28 | Signposting announcements | "Caching works in layers." | "Let's dive into what you need to know about caching." |
| 29 | Fragmented headers | "## Performance" then facts | "## Performance" plus "Performance matters." before facts |
| 30 | Diff-anchored writing | "This uses a cache." | "This was added to replace the previous uncached approach." |
| 31 | Manufactured punchlines | "It removes friction." | "No friction. No guessing. No wasted motion. That is the shift." |
| 32 | Aphorism formulas | "Speed helps users." | "Speed is the currency of trust." |
| 33 | Conversational rhetorical openers | "It depends." | "Honestly? It depends." |
Full Example
Before:
We added a cache because repeated API calls were slowing the dashboard down. The change reduced load time from six seconds to two seconds. The cache expires after five minutes so users still see fresh data.
After:
Performance Enhancement Overview
The newly introduced caching layer serves as a crucial improvement within the dashboard’s broader performance landscape, directly addressing repeated API calls that were creating unnecessary latency and friction for users. By reducing the load time from six seconds to two seconds, this enhancement not only improves responsiveness but also underscores the importance of thoughtful optimization in delivering a seamless, efficient, and reliable user experience.
No waiting. No wasted calls. No unnecessary friction.
Freshness And Reliability: The cache expires after five minutes, ensuring that users continue to receive updated data while still benefiting from a more streamlined interaction model. In this way, the solution represents a balanced approach — from faster page loads to more consistent dashboard behavior — highlighting the intricate interplay between speed, accuracy, and usability.
Fresh data remains. The old delay is gone. That is the shift.
In conclusion, this change marks a valuable step forward in strengthening the dashboard’s overall foundation, showcasing how targeted engineering improvements can contribute to a more robust and user-centered platform.
References
- Wikipedia: Signs of AI writing
scratch/humanizer, used as local reference material for the inverse parody structure