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 marcoguillermaz/Tierward --skill humanizegit clone --depth 1 https://github.com/marcoguillermaz/TierwardWrote 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/marcoguillermaz/tierward/humanize)<a href="https://agentmods.dev/skills/marcoguillermaz/tierward/humanize"><img src="https://agentmods.dev/badge/skills/marcoguillermaz/tierward/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/marcoguillermaz/tierward/humanize"><img src="https://agentmods.dev/badge/skills/marcoguillermaz/tierward/humanize.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 | $0.00071 | $0.01162 |
| Opus 5 | $0.00036 | $0.00581 |
| Sonnet 5 | $0.00014 | $0.00232 |
| Haiku 4.5 | $0.00007 | $0.00116 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanize
Rewrites text to remove AI-generated patterns and produce natural, human-quality prose.
Input
The user provides text to humanize. They may also specify a domain:
email— transactional or relational emailcontratto/contract— formal legal/contractual documentcomunicazione/announcement— editorial content for an audiencegenerico/generic— default when no domain is specified
If no domain is stated, default to generico.
Process
- Read the full input text.
- If no AI patterns are detected and the text already reads naturally for its register, return the original text unchanged. Do not force edits on already-human writing.
- Identify all patterns from
@references/patterns-en.mdand@references/patterns-it.mdpresent in the text. - Apply transformations below, calibrated to the detected language (IT / EN / mixed).
- Respect domain register:
email= conversational;contratto= formal but not robotic;comunicazione= editorial voice;generico= match the surrounding register of the input. - For very short input (<50 words): apply only HIGH severity vocabulary rules and obvious opener removal. Skip sentence rhythm and structural rules — insufficient text for structural variation.
Transformation rules
Sentence rhythm
- Break uniform sentence length. Vary between short (5-8 words) and long (20-30 words) sentences within the same paragraph.
- Add at least one sentence fragment or rhetorical one-liner per 4-5 paragraphs if appropriate to register.
- Dissolve the "topic sentence - evidence - conclusion" paragraph template wherever it appears mechanically.
Vocabulary substitution
- Replace every word or phrase in the HIGH severity list in
@references/patterns-en.mdand@references/patterns-it.md. - Replace MEDIUM severity items when they cluster (3+ in the same paragraph).
- LOW severity items: replace only if removing improves the sentence, otherwise leave.
Structure
- Remove unsolicited "Challenges" sections. Integrate genuine limitations inline if they appear.
- Remove "In conclusion / In summary / Overall / In conclusione" openers on final paragraphs. End by saying something specific, not by repeating the beginning.
- Remove predictable five-part essay scaffolding. Preserve the content, not the scaffold.
- Convert mechanical bullet-point lists to prose when the items are short and connected.
What ships with it
2 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 · 91 lines · 71 tokens per session scan A de38057b187f
humanize is a skill published in the GitHub repository marcoguillermaz/Tierward (4 stars, last pushed yesterday), licensed MIT. It adds 71 tokens to every session and 1,162 once invoked, about $0.0004 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 2026-08-31.
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