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 EliasOulkadi/shokunin --skill humanizegit clone --depth 1 https://github.com/EliasOulkadi/shokuninWrote 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/eliasoulkadi/shokunin/humanize)<a href="https://agentmods.dev/skills/eliasoulkadi/shokunin/humanize"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/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/eliasoulkadi/shokunin/humanize"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/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 | $0.00056 | $0.02507 |
| Opus 5 | $0.00028 | $0.01254 |
| Sonnet 5 | $0.00011 | $0.00501 |
| Haiku 4.5 | $0.00006 | $0.00251 |
Grade A, and why
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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
humanize · 人間
人間 · にんげん — "human being". Makes AI-generated text sound like a real person wrote it.
Based on research from: Grammarly, MIT Technology Review, GPTZero, QuillBot, Reddit (r/auscorp, r/cybersecurity), Hacker News, Stack Overflow, JustDone, print-css.rocks, BrowserStack, pdf4.dev benchmarks, and professional writing guides (2024–2026).
Core metrics AI detectors measure
| Metric | What it means | Human text | AI text |
|---|---|---|---|
| Perplexity | How predictable each word is | High — uses unexpected words | Low — always picks the most probable word |
| Burstiness | Variance in sentence length | High — mixes short/long sentences | Low — uniform sentence length |
| Word frequency | Rate of common vs rare words | Balanced — uses uncommon terms | Skewed — overuses "the", "it", "is" |
| Repetition | Recurring patterns | Low — natural variation | High — same structures repeat |
Sources: GPTZero, QuillBot, MIT Technology Review, Google Brain research (Ippolito et al. 2020)
The 16 AI tells (how to spot them)
1. Overused buzzwords (Grammarly 2026, Reddit)
| AI word | Human alternative |
|---|---|
| delve into | analyze, explore, dig into |
| pivotal | key, decisive, critical |
| underscore | highlight, point out, stress |
| multifaceted | complex, with several aspects |
| landscape | ecosystem, context, situation |
| paradigm | model, approach, framework |
| robust | solid, reliable, resilient |
| leverage | use, harness, take advantage of |
| seamless | smooth, frictionless, natural |
| transformative | disruptive, profound, radical |
2. Mechanical connectors (GPTZero research)
- "Moreover", "Furthermore", "Nevertheless", "Consequently" → use "Also", "But", "So" or nothing
- "However" every 3 paragraphs → cut half, let it flow
- "Nevertheless", "Therefore", "Consequently" → replace with "So", "Then", "That means"
3. Perfect symmetrical structure (MIT Tech Review)
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 First seen · 270 lines · 56 tokens per session scan A 9b20a5b7a24d
humanize is a skill published in the GitHub repository EliasOulkadi/shokunin (113 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 2,507 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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