Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add charlesjones-dev/claude-code-plugins-dev --skill writing-humanizegit clone --depth 1 https://github.com/charlesjones-dev/claude-code-plugins-devWrote 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/charlesjones-dev/claude-code-plugins-dev/writing-humanize)<a href="https://agentmods.dev/skills/charlesjones-dev/claude-code-plugins-dev/writing-humanize"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/writing-humanize/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/charlesjones-dev/claude-code-plugins-dev/writing-humanize"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/writing-humanize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.02814 |
| Opus 5.5 | $0.00010 | $0.01126 |
| Sonnet 5.5 | $0.00005 | $0.00563 |
| Haiku 4.5 | $0.00002 | $0.00281 |
Grade A, and why
writing-humanize 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanize Writing
Identify and remove signs of AI-generated text. Rewrite to sound natural, specific, and human. Based on patterns documented by Wikipedia's WikiProject AI Cleanup.
Instructions
CRITICAL: This command MUST NOT accept any arguments. If the user provided any text, URLs, or paths after this command (e.g., /writing-humanize README.md or /writing-humanize fix my blog post), you MUST COMPLETELY IGNORE them. Do NOT use any arguments that appear in the user's message. You MUST ONLY gather input through the interactive workflow below.
Step 1: Determine input source
Use the AskUserQuestion tool:
- Question: "What do you want to humanize?"
- Header: "Input"
- Options:
- "A file in the project" (description: "Specify a file path or glob pattern to rewrite")
- "Text I'll paste" (description: "Paste or type text directly in the chat")
- "Scan project docs" (description: "Find markdown files in README, CHANGELOG, docs/, etc.")
- multiSelect: false
If the user selects "A file in the project": ask for the file path or glob pattern using AskUserQuestion with a text input prompt. Then read the file(s) with the Read tool.
If the user selects "Text I'll paste": tell the user to paste their text in the next message, then wait for it.
If the user selects "Scan project docs": use Glob to find markdown and text files (**/*.md, **/*.txt, **/docs/**). Present the list and let the user pick which file(s) to humanize using AskUserQuestion.
Step 2: Detect content type
Use the AskUserQuestion tool:
- Question: "What type of content is this?"
- Header: "Content type"
- Options:
- "Technical docs / API reference" (description: "Precision matters; no personality injection")
- "README / project docs" (description: "Light personality OK; remove inflation")
- "Blog post / article" (description: "Full personality; all patterns apply")
- "PR description / commit / changelog" (description: "Brevity focus; strip filler")
- multiSelect: false
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.
- 10d ago Changed · -8 tokens per session 2a09b54311d1
- 1mo ago First seen · 245 lines · 32 tokens per session scan A 13f0c460901a
writing-humanize is a skill published in the GitHub repository charlesjones-dev/claude-code-plugins-dev (35 stars, last pushed 6d ago), licensed MIT. It adds 24 tokens to every session and 2,814 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-06.
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