Borrowing it
Nothing to install: this file belongs to Cerlancism/wenyan.skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Cerlancism/wenyan.skill/main/.agents/skills/humanizer/SKILL.mdgit clone --depth 1 https://github.com/Cerlancism/wenyan.skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cerlancism/wenyan.skill/humanizer)<a href="https://agentmods.dev/skills/cerlancism/wenyan.skill/humanizer"><img src="https://agentmods.dev/badge/skills/cerlancism/wenyan.skill/humanizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cerlancism/wenyan.skill/humanizer"><img src="https://agentmods.dev/badge/skills/cerlancism/wenyan.skill/humanizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00093 | $0.06537 |
| Opus 5 | $0.00046 | $0.03268 |
| Sonnet 5 | $0.00019 | $0.01307 |
| Haiku 4.5 | $0.00009 | $0.00654 |
Grade A, and why
humanizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to humanizer — 204 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 588 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanizer: 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 - Don't 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
Voice Calibration (Optional)
If the user provides a writing sample (their own previous writing), analyze it before rewriting:
-
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?)
-
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."
-
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."
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 588 lines · 93 tokens per session scan A 37c4b5ca0957
humanizer is a skill published in the GitHub repository Cerlancism/wenyan.skill (2 stars, last pushed 4mo ago), licensed MIT. It adds 93 tokens to every session and 6,537 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to humanizer, differing in 204 lines, and is treated as a copy.
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