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 Natsummerance/readMD --skill e2e92e7b4b8229253ed5c8e81dc65463fdeddda5git clone --depth 1 https://github.com/Natsummerance/readMDWrote 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/natsummerance/readmd/e2e92e7b4b8229253ed5c8e81dc65463fdeddda5)<a href="https://agentmods.dev/skills/natsummerance/readmd/e2e92e7b4b8229253ed5c8e81dc65463fdeddda5"><img src="https://agentmods.dev/badge/skills/natsummerance/readmd/e2e92e7b4b8229253ed5c8e81dc65463fdeddda5/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/natsummerance/readmd/e2e92e7b4b8229253ed5c8e81dc65463fdeddda5"><img src="https://agentmods.dev/badge/skills/natsummerance/readmd/e2e92e7b4b8229253ed5c8e81dc65463fdeddda5.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 | $0.00061 | $0.06633 |
| Opus 5 | $0.00030 | $0.03317 |
| Sonnet 5 | $0.00012 | $0.01327 |
| Haiku 4.5 | $0.00006 | $0.00663 |
Grade A, and why
humanizer scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Curly quotes alone.** macOS, Word, Google Docs, and most CMSes auto-curl by default. Curly quotes only count when stacked with other tells. This is a copy
100% identical to humanizer — 542 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 — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanizer: remove AI writing patterns
Rewrite AI-sounding text so it reads like the writer, not a chatbot. Do not change what it says or make up details.
The patterns below come from Wikipedia's "Signs of AI writing", maintained by WikiProject AI Cleanup.
What to do
When given text to humanize:
- Find AI patterns. Check the text against the patterns below.
- Keep every claim. You may shorten dull parts, expand useful parts, and merge or split paragraphs. Keep the information even when you change the structure.
- Do not invent facts. Do not add a fact, name, number, date, quote, or citation unless it comes from the source or the user. If a sentence needs a missing detail, ask for it or use a simpler sentence. You may add an opinion or reaction when the writer's voice calls for one, but you may not add a factual claim. Fiction is exempt because invented details are part of the task.
- Match the voice. Use the right tone for the text, such as formal, casual, or technical. Add personality only when the text and the writer call for it.
The input type controls what you return. See How to return the result. Use the same rewrite process in every mode.
Match the writer's voice
If the user provides a writing sample (their own previous writing), analyze it before rewriting:
- Read the sample first. Note its sentence length, word choice, paragraph openings, punctuation, repeated phrases, and transitions.
- Match those habits. Do not replace casual words with formal ones or remove deliberate quirks.
- If there is no sample, use the guidance below.
A writing sample takes priority over these style rules. If the sample uses em dashes, keep them at about the same rate. Do not apply §14 as a ban.
Add personality only when it fits
Removing AI patterns is only half the job. The result should still sound like a person.
Use personality in blog posts, essays, opinions, and personal writing when it fits the writer. Keep reference, technical, legal, and factual text neutral. Do not add opinions or first-person language where they do not belong.
What ships with it
8 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.
- 11d ago First seen · 457 lines · 61 tokens per session scan A 14fc8a965b6e
humanizer is a skill published in the GitHub repository Natsummerance/readMD (22 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 6,633 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to humanizer, differing in 542 lines, and is treated as a copy.
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