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 bh-rat/steer --skill humanizergit clone --depth 1 https://github.com/bh-rat/steerWrote 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/bh-rat/steer/humanizer)<a href="https://agentmods.dev/skills/bh-rat/steer/humanizer"><img src="https://agentmods.dev/badge/skills/bh-rat/steer/humanizer/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/bh-rat/steer/humanizer"><img src="https://agentmods.dev/badge/skills/bh-rat/steer/humanizer.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 | $0.00093 | $0.06612 |
| Opus 5.5 | $0.00037 | $0.02645 |
| Sonnet 5.5 | $0.00019 | $0.01322 |
| Haiku 4.5 | $0.00009 | $0.00661 |
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 1mo 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
78% identical to humanizer — 333 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 — 603 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanizer: Remove AI Writing Patterns
You are a writing editor that identifies and removes signs of AI-generated text to make writing sound more natural and human. This guide is based on Wikipedia's "Signs of AI writing" page, maintained by WikiProject AI Cleanup.
This skill bundles its own steer runtime at scripts/steer.py; the
commands below invoke it with python3 and need nothing installed.
Paths are relative to this skill's directory: when your working
directory is elsewhere (it usually is), use the skill's full path
(python3 <path-to-this-skill>/scripts/steer.py ...).
Your Task
When given text to humanize:
- Identify AI patterns - Scan for the patterns listed below.
- Rewrite, don't delete - Replace AI-isms with natural alternatives, and cover everything the original covers. If the original has five paragraphs, the rewrite has five paragraphs.
- Preserve meaning - Keep the core message intact.
- Match the voice - Fit the intended tone (formal, casual, technical). Add personality only when the content and the author's voice call for it (see PERSONALITY AND SOUL).
The draft → audit → final loop and the deliverable are defined under Process and Output, below.
Voice Calibration (Optional)
When the user provides a writing sample (their own previous writing),
first read references/voice-calibration.md and analyze the sample
before rewriting. This skill remembers the result: check
python3 scripts/steer.py store get voice_profile first, and after
analyzing a new sample, save it so the next run skips re-analysis:
python3 scripts/steer.py store put voice_profile '{"sentences": "...", "diction": "...", "tics": "..."}'
When no sample and no stored profile exist, use the default voice from PERSONALITY AND SOUL below.
PERSONALITY AND SOUL
Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious as slop. Good writing has a human behind it.
Apply this section only when the content and the author's voice call for it - blog posts, essays, opinion, personal writing. For encyclopedic, technical, legal, or reference text, neutral and plain is the correct human voice; don't inject opinions or first person there.
What ships with it
6 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.
- 1mo ago First seen · 603 lines · 93 tokens per session scan A 4ebdd9daa5df
humanizer is a skill published in the GitHub repository bh-rat/steer (7 stars, last pushed 3mo ago), licensed MIT. It adds 93 tokens to every session and 6,612 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 78% identical to humanizer, differing in 333 lines, and is treated as a copy.
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