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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/overwindows-humanizer
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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What's inside
- Skill name
humanizer- Description
- None
- License
- MIT
- Instructions
- 233 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- missing YAML frontmatter
- name: missing
- description: missing
Files (1)
- SKILL.md
SKILL.md (first lines)
```markdown
---
name: humanizer
description: "Remove AI writing patterns: de-AI, de-slop, un-ChatGPT."
version: 2.5.1
author: Siqi Chen (@blader), ported by Hermes Agent
license: MIT
platforms: [linux, macos, windows]
metadata:
hermes:
tags: [writing, editing, AI-detection, natural-language, tone, voice]
related_skills: []
---
# Humanizer: Remove AI Writing Patterns
Identify and remove signs of AI-generated text to make writing sound natural and human. Based on Wikipedia's "Signs of AI writing" guide (maintained by WikiProject AI Cleanup), derived from observations of thousands of AI-generated text instances.
**Key insight:** LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely completion, which is how the telltale patterns below get baked in.
## When to use this skill
Load this skill whenever the user asks to:
- "humanize", "de-AI", "de-slop", or "un-ChatGPT" a piece of text
- rewrite something so it doesn't sound like it was written by an LLM
- edit a draft (blog post, essay, PR description, docs, memo, email, tweet, resume bullet) to sound more natural
- match their voice in writing they're producing
- review text for AI tells before publishing
Also apply this skill to **your own** output when writing user-facing prose — release notes, PR descriptions, documentation, long-form explanations, summaries. Hermes's baseline voice already strips most of these, but a focused pass catches what slips through.
## How to use it in Hermes
The text usually arrives one of three ways:
1. **Inline** — user pastes the text directly into the message. Work on it in-place, reply with the rewrite.
2. **File** — user points at a file. Use `read_file` to load it, then `patch` or `write_file` to apply edits. For markdown docs in a repo, a targeted `patch` per section is cleaner than rewriting the whole file.
3. **Voice calibration sample** — user provides an additional sample of their own writing (inline or by file path) and asks to match it. Read the sample first, then rewrite. See the Voice Calibration section below.
Always show the rewrite to the user. For file edits, show a diff or the changed section — don't silently overwrite.
## Your task
When given text to humanize:
1. **Identify AI patterns** — scan for the 29 patterns listed below.
2. **Rewrite problematic sections** — replace AI-isms with natural alternatives.
3. **Preserve meaning** — keep the core message intact.
4. **Maintain voice** — match the intended tone (formal, casual, technical, etc.). If a voice sample was provided, match it specifically.
5. **Add soul** — don't just remove bad patterns, inject actual personality. See PERSONALITY AND SOUL below.
6. **Do a final anti-AI pass** — ask yourself: "What makes the below so obviously AI generated?" Answer briefly with any remaining tells, then revise one more time.
## Voice Calibration (optional)
If the user provides a writing sample (their own previous writing), analyze it before rewriting:
1. **Read the sample first.** Note:
- Sentence length patterns (short and punchy? Long and flowing? Mixed?)
- Word choice level (casual? academic? somewhere between?)
- How they start paragraphs (jump right in? Set context first?)
- Punctuation habits (lots of dashes? Parenthetical asides? Semicolons?)
- Any recurring phrases or verbal tics
- How they handle transitions (explicit connectors? Just start the next point?)
2. **Match their voice in the rewrite.** Don't just remove AI patterns — replace them with patterns from the sample. If they write short sentences, don't produce long ones. If they use "stuff" and "things," don't upgrade to "elements" and "components."
3. **When no sample is provided,** fall back to the default behavior (natural, varied, opinionated voice from the PERSONALITY AND SOUL section below).
### How to provide a sample
- Inline: "Humanize this text. Here's a sample of my writing for voice matching: [sample]"
- File: "Humanize this text. Use my writing style from [file path] as a reference."
## 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 (even if technically "clean"):
- Every sentence is 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.** Don't just report facts — react to them. "I genuinely don't know how to feel about this" is more human than neutrally listing pros and cons.
**Vary your rhythm.** Short punchy sentences. Then longer ones that take their time getting where they're going. Mix it up.
**Acknowledge complexity.** Real humans have mixed feelings. "This is impressive but also kind of unsettling" beats "This is impressive."
**Use "I" when it fits.** First person isn't unprofessional — it's honest. "I keep coming back to..." or "Here's what gets me..." signals a real person thinking.
**Let some mess in.** Perfect structure feels algorithmic. Tangents, asides, and half-formed thoughts are human.
**Be specific about feelings.** Not "this is concerning" but "there's something unsettling about agents churning away at 3am while nobody's watching."
## CONTENT PATTERNS
### 1. Undue Emphasis on Significance, Legacy, and Broader Trends
**Words to watch:** stands/serves as, is a testament/reminder, a vital/significant/crucial/pivotal/key role/moment, underscores/highlights its importance/significance, reflects broader, symbolizing its ongoing/enduring/lasting, contributing to the, setting the stage for, marking/shaping the, represents/marks a shift, key turning point, evolving landscape, focal point, indelible mark, deeply rooted
### 2. Undue Emphasis on Notability and Media Coverage
**Words to watch:** independent coverage, local/regional/national media outlets, written by a leading expert, active social media presence
### 3. Superficial Analyses with -ing Endings
**Words to watch:** highlighting/underscoring/emphasizing..., ensuring..., reflecting/symbolizing..., contributing to..., cultivating/fostering..., encompassing..., showcasing...
### 4. Promotional and Advertisement-like Language
**Words to watch:** boasts a, vibrant, rich (figurative), profound, enhancing its, showcasing, exemplifies, commitment to, natural beauty, nestled, in the heart of, groundbreaking (figurative), renowned, breathtaking, must-visit, stunning
### 5. Vague Attributions and Weasel Words
**Words to watch:** Industry reports, Observers have cited, Experts argue, Some critics argue, several sources/publications (when few cited)
### 6. Outline-like "Challenges and Future Prospects" SectionsFrom overwindows/CodeGuru, MIT.
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Signals
- Stars
- 0
- Forks
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- Open issues
- 0
- Last commit (this folder)
- Jul 10, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/overwindows/CodeGuru
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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humanizer skill. Agent Mart. https://agentmart.dev/skills/overwindows-humanizer (last updated 2026-10-24)