humanizer
Skill1 starsChanged 2 months agoMITView on GitHub
Use when stripping AI writing patterns, corporate fluff, and synthetic tone from drafts to restore natural human cadence.
188 other projects use a version of this.
Adopted by
Most recently taken up by
- aditya-vermax/skillstheir own version, first seen Nov 8, 2026
- chrisleekr/skillstheir own version, first seen Nov 8, 2026
- xhqing/CommunityManagerAgenttheir own version, first seen Nov 8, 2026
- CloudChef/atlasclaw-providerstheir own version, first seen Nov 8, 2026
- Fractera/Agent-Engineering-Infrastructuretheir own version, first seen Nov 8, 2026
- Fractera/Agentic-Engineering-Infrastructuretheir own version, first seen Nov 8, 2026
Used with
Projects with it also use economy-mode, personal-voice and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
Microsoft AzureSkilleconomy-mode
Shifts Layer 3 model selection to cost-optimized alternatives when economy mode is active.
Also in 4 projects that use this
petermuirurithuoSkillpersonal-voice
Captures the user's personality, communication style, and values. Use this skill whenever responding to the user, drafting anything on their behalf (emails, CVs, messages, opinions, explanations), or whenever tone, word choice, or how an opinion is delivered matters. Apply it by default for any prompt, not only when the user explicitly asks for "my style" or "my voice.
Also in 3 projects that use this
- Microsoft AzureSkill
architectural-proposals
How to write comprehensive architectural proposals that drive alignment before code is written
Also in 3 projects that use this
- +9 more from Azure
Other versions188 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 188
- NousResearch/hermes-agent★ 262ksame name
- blader/humanizer★ 63ksame name
- QuivrHQ/quivr★ 40ksame name
- The-Vibe-Company/quivr★ 40ksame name
- rommapp/romm★ 14ksame name
- github/gh-aw★ 5.6ksame name
- latitude-dev/latitude-llm★ 4.7ksame name
- github/squad★ 3.4ksame name
- compozy/compozy★ 2.9ksame name
- SRombauts/SQLiteCpp★ 2.8ksame name
178 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 175 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 42
Changing factual meaning during simplification: Ensure technical parameters, numbers, and commands remain identical.
“Common” is measured: kept by at least 6 in 10 of the 175 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Text Humanizer & Anti-AI Tone Filter
Overview
A specialized text purification skill that systematically scans, detects, and purges syntactic and semantic markers of LLM-generated text, transforming stiff output into natural, authentic human communication.
When to Use & When NOT to Use
When to Use
- Rewriting LLM output for developer blogs, emails, announcements, and documentation.
- Removing excessive hedging ("it may be beneficial to consider...") and passive voice.
- Enforcing concise, punchy technical communication.
When NOT to Use
- Translating structured data tables or code blocks.
- Tasks requiring formal academic third-person passive syntax.
Transformation Matrix
| LLM Pattern | Why It Feels Synthetic | Transformation Strategy |
| Sycophantic Agreement | "You make a great point! Absolutely..." | Delete entirely; answer the question directly |
| Rule-of-Three Adjectives | "Seamless, robust, and scalable solution" | Use one precise, factual description |
| Passive Hedging | "It could potentially be argued that..." | "In our tests, X caused Y." |
| Synthetic Summaries | "By following these steps, you will unlock..." | Replace with a concise summary table or next actions |
Common Pitfalls
- Replacing AI fluff with informal slang: Maintain professional engineering rigor while removing robotic phrasing.
- Changing factual meaning during simplification: Ensure technical parameters, numbers, and commands remain identical.
Verification Checklist
- Removed all instances of sycophantic opening filler.
- Converted passive hedges into direct, verifiable statements.
- Maintained 100% of original technical facts and parameter values.
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