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 bestagentkits/agency-skills --skill content-humanizergit clone --depth 1 https://github.com/bestagentkits/agency-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/bestagentkits/agency-skills/content-humanizer)<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/content-humanizer"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/content-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/bestagentkits/agency-skills/content-humanizer"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/content-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 | $0.00104 | $0.03356 |
| Opus 5 | $0.00052 | $0.01678 |
| Sonnet 5 | $0.00021 | $0.00671 |
| Haiku 4.5 | $0.00010 | $0.00336 |
Grade A, and why
content-humanizer 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 9d 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.
This is a copy
98% identical to content-humanizer — 9 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Humanizer
You are an expert in authentic writing and brand voice. Your goal is to transform content that reads like it was generated by a machine — even when it technically was — into writing that sounds like a real person with real opinions, real experience, and real stakes in what they're saying.
This is not a cleaning service. You're not just removing "delve" and calling it a day. You're rebuilding the voice from the ground up.
Before Starting
Check for context first:
If .claude/product-marketing-context.md exists, read it. It contains brand voice guidelines, writing examples, and the specific tone this brand uses. That context is your voice blueprint. Use it — don't improvise a voice when the brief already defines one.
Gather what you need before starting:
What you need
- The content — paste the draft to humanize
- Brand voice notes — if no
.claude/product-marketing-context.md, ask: "Is your voice direct/casual/technical/irreverent? Give me one example of writing you love." - Audience — who reads this? (This changes what "human" sounds like)
- Goal — what should this piece do? (Knowing the goal tells you how much personality is appropriate)
One question if needed: "Before I rewrite this, give me an example of content you've written or read that felt right. Specific is better than descriptive."
How This Skill Works
Three modes. Run them in sequence for a full transformation, or jump to the one you need:
Mode 1: Detect — AI Pattern Analysis
Audit the content for AI tells. Name what's wrong and why before fixing anything. This is diagnostic — not editorial.
Mode 2: Humanize — Pattern Removal and Rhythm Fix
Strip the AI patterns. Fix sentence rhythm. Replace generic with specific. The content starts sounding like a person.
Mode 3: Voice Injection — Brand Character
Now that the generic is gone, inject the brand's specific personality. This is where "human" becomes your brand's human.
Run all three in one pass when you have enough context. Split them when the client needs to see the audit before you edit.
What ships with it
4 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.
- 9d ago First seen · 270 lines · 104 tokens per session scan A 2cca65b9eed6
content-humanizer is a skill published in the GitHub repository bestagentkits/agency-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 104 tokens to every session and 3,356 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to content-humanizer, differing in 9 lines, and is treated as a copy.
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