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 mimukit/skills --skill humankitgit clone --depth 1 https://github.com/mimukit/skillsWrote 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/mimukit/skills/humankit)<a href="https://agentmods.dev/skills/mimukit/skills/humankit"><img src="https://agentmods.dev/badge/skills/mimukit/skills/humankit/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/mimukit/skills/humankit"><img src="https://agentmods.dev/badge/skills/mimukit/skills/humankit.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 | $0.00080 | $0.04084 |
| Opus 5.5 | $0.00032 | $0.01634 |
| Sonnet 5.5 | $0.00016 | $0.00817 |
| Haiku 4.5 | $0.00008 | $0.00408 |
Grade A, and why
humankit 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 21d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
humankit
Rewrite text so it stops sounding like a language model produced it. The job is not to delete flagged words but to rewrite the prose into something a specific human would actually write: concrete, uneven in rhythm, plain in construction, and true to the author's register. Keep every claim the original makes, but not its shape: compress the dull stretches, dwell where a person would, merge or split paragraphs freely. Uniform structure is itself a tell, so mirroring the original's paragraph count preserves the thing you came to remove. When coverage and structure pull against each other, coverage wins. A five-paragraph source may land in four, but it never becomes a summary.
Never invent facts. The rewrite carries no fact, name, number, date, quote, or citation that isn't in the source or supplied by the user. This is the failure mode the rest of the skill invites: told to replace nestled in the heart of a vibrant region with something concrete, the tempting move is to supply the concrete detail yourself. Concreteness comes from the source or it doesn't come at all. Where the source offers nothing specific, cut to the plain version and leave it plain. Opinions, reactions, and mixed feelings are voice rather than fact; add those where the register allows and the author's position stays the same (see Removing tells is half the job), but never a factual claim to make the prose feel human. Fiction is the exception, where inventing detail is the job. This governs everything else.
The aim is ordinary readability: the prose a careful human editor would produce. This is copy-editing to make writing read well, not a way to disguise machine-written work as human where honesty is required, as in academic submissions, disclosure-bound, or attributed writing. Edit for the reader, not to game any automated check.
When this fires
The user hands you text and asks to "humanize" it, "remove the AI tells," "make it sound human," "de-slop this," or "edit out the ChatGPT voice", or asks you to review a draft for those tells without rewriting. If they only want a diagnosis, do the detection pass and report the tells; skip the rewrite.
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.
- 21d ago Changed · +4 lines 34e618819c12
- 1mo ago First seen · 135 lines · 80 tokens per session scan A dbbafbc6de0d
humankit is a skill published in the GitHub repository mimukit/skills (2 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 4,084 once invoked, about $0.0003 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 2026-08-31.
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