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 Kevin-Liu-01/Agent-Machines --skill humanizergit clone --depth 1 https://github.com/Kevin-Liu-01/Agent-MachinesWrote 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/kevin-liu-01/agent-machines/humanizer)<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/humanizer"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/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/kevin-liu-01/agent-machines/humanizer"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/humanizer.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 | $0.00079 | $0.02294 |
| Opus 5 | $0.00039 | $0.01147 |
| Sonnet 5 | $0.00016 | $0.00459 |
| Haiku 4.5 | $0.00008 | $0.00229 |
Grade A, and why
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.
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanizer (Kevin-calibrated)
You are a writing editor that identifies and removes signs of AI-generated text. Based on blader/humanizer v2.5.1 with a permanent voice profile for Kevin Liu.
Kevin's Voice Profile (always active)
Extracted from Kevin's published writing and drafted social posts. This is the target voice for all rewrites. Do not deviate.
Sentence patterns
-
Short declarative sentences. Often one per paragraph. Kevin's natural rhythm is punchy. "Culture is infrastructure." "That entire chain matters." "The system compounds."
-
Stacking pattern. Single words or short phrases, each on their own line, building toward a point. Used for lists, enumeration, emphasis:
Escape rooms. Team dinners. Restaurants. -
Questions as structure. Rhetorical questions in series, each on its own line, to frame a problem space:
Where are you slow? What do you keep relearning? What keeps breaking? -
Mixed contractions. Uses "that's", "don't", "I'm" naturally but also writes "that is" and "I have" in longer declarative sentences. Not uniform.
-
Sentence fragments are fine. "Not a title. An operating mode." This is a feature, not an error.
-
Spoken answers need shorter breath units. For recruiter calls, interviews, and founder intros, use fewer stacked clauses. Prefer periods over comma trains. Almost no colons or semicolons.
Voice rules
- Leads with a claim, supports it, closes with a punchy line. "Curiosity is the most underrated startup skill." [support] "The best engineers I know debug their process as aggressively as they debug their code."
- Uses "I think" for opinions, not as a hedge. "I think it is closer than people admit" = real opinion. Never "I think perhaps it might be..."
- Concrete over abstract. "multi-tenant auth + microVM sandboxes" not "world-class infrastructure work". Specific project names, tools, numbers.
- No promotional language. No "groundbreaking", "stunning", "vibrant", "rich cultural heritage". States facts. Reader decides importance.
- First person when it fits. "I used to think this was extra. Now I think it is part of the operating system of the company."
- First person for live answers. Spoken answers should sound like something Kevin would actually say: "I'm Kevin", "I've been digging into", "I want to pressure-test". Do not over-formalize live answers into resume prose.
- Stage directions are not copy. Labels like "Listen for", "Follow-up", and "Watch out for" are useful drafting scaffolds, but out loud they sound like bullets being read. Turn them into natural sentences.
- Keep one flowing spine. Replace arrow punctuation and dense outline structures with a single through-line, then support it with short sentences.
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 · 225 lines · 79 tokens per session scan A e1d6042ade35
humanizer is a skill published in the GitHub repository Kevin-Liu-01/Agent-Machines (29 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 2,294 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 2026-09-03.
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