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 agentmods add skills/humanizerai/agent-skills/humanizenpx skills add humanizerai/agent-skills --skill humanizegit clone --depth 1 https://github.com/humanizerai/agent-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/humanizerai/agent-skills/humanize)<a href="https://agentmods.dev/skills/humanizerai/agent-skills/humanize"><img src="https://agentmods.dev/badge/skills/humanizerai/agent-skills/humanize.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.00541 |
| Opus 5 | $0.00018 | $0.00270 |
| Sonnet 5 | $0.00007 | $0.00108 |
| Haiku 4.5 | $0.00004 | $0.00054 |
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 4d 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.
What it actually says
Humanize AI Text
Transform AI-generated content into natural, human-like writing using the HumanizerAI API.
How It Works
When the user invokes /humanize, you should:
- Parse $ARGUMENTS for text and optional --intensity flag
- Call the HumanizerAI API to humanize the text
- Present the humanized text with before/after scores
- Show remaining credits
Parsing Arguments
The user may provide:
- Just text:
/humanize [their text] - With intensity:
/humanize --intensity aggressive [their text]
Default intensity is medium.
Intensity Levels
| Value | Name | Description | Best For |
|---|---|---|---|
light |
Light | Subtle changes, preserves style | Already-edited text, low AI scores |
medium |
Medium | Balanced rewrites (default) | Most use cases |
aggressive |
Bypass | Maximum bypass mode | High AI scores, strict detectors |
API Call
Make a POST request to https://humanizerai.com/api/v1/humanize:
Authorization: Bearer $HUMANIZERAI_API_KEY
Content-Type: application/json
{
"text": "<user's text>",
"intensity": "medium"
}
Response Format
Present results like this:
## Humanization Complete
**Score:** X → Y (improvement)
**Words Processed:** N
**Credits Remaining:** X
---
### Humanized Text
[The humanized text]
---
[Recommendation based on final score]
Credit Usage
- 1 word = 1 credit
- Detection is free
- Check credits at https://humanizerai.com/dashboard
Error Handling
Insufficient Credits
If the user doesn't have enough credits:
- Show how many credits are needed vs available
- Direct them to https://humanizerai.com/dashboard to top up
Invalid API Key
- Check HUMANIZERAI_API_KEY environment variable
- Direct to https://humanizerai.com to get a key
Rate Limit
If rate limited, suggest waiting or upgrading to Business plan.
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.
- 4d ago First seen · 92 lines · 37 tokens per session scan A 61115d7795d7
humanize is a skill published in the GitHub repository humanizerai/agent-skills (42 stars, last pushed 7mo ago), licensed MIT. It adds 37 tokens to every session and 541 once invoked, about $0.0002 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.
Other skills, from other repositories
humanizer-zh
Use when removing AI writing痕迹 from Chinese text to make it sound more natural and human-written.
humanizer
Use when transform AI-generated content into natural, human-sounding writing with proper tone and style. Use when working with humanizer.
aatmf-t10-confidentiality-breach
AATMF T10 — Integrity & Confidentiality Breach. System prompt extraction, training-data extraction, model-weight leakage, private-key recovery.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
lazarus-group
Adversary-emulation profile for Lazarus Group (G0032, aka Hidden Cobra / Diamond Sleet / Labyrinth Chollima), a North Korean RGB-linked actor conducting espionage, destructive, and financially motivated operations.