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 voicegit 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/voice)<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/voice"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/voice/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/voice"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/voice.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 | $0.00156 | $0.01890 |
| Opus 5 | $0.00078 | $0.00945 |
| Sonnet 5 | $0.00031 | $0.00378 |
| Haiku 4.5 | $0.00016 | $0.00189 |
Grade A, and why
voice 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Voice
Third-person positioning voice. Modeled on the credential-forward "Why?" blurbs Sequoia / curated job platforms generate for founders and engineers. Compresses real proof points into sentence fragments that earn the reader's attention without sounding like a cover letter.
Scope: self-positioning only. Bios, blurbs, headlines, openers, About sections.
- For social posts in the subject's voice ->
social-draft - For generic marketing copy ->
copywriting
Source of Truth (read every time)
Before writing anything, load the subject's source-of-truth files (their wiki, profile doc, resume, and any past public bios). Never invent a fact, company, metric, or title. If the proof isn't there, ask or use a different angle.
| File | What it has |
|---|---|
USER.md (or equivalent) |
Identity, current work, strengths, key people |
career-profile.md (if any) |
Positioning, target roles, differentiators |
resume.md (if any) |
Companies, dates, bullets, metrics, publications |
If any of these are stale or missing, surface the gap before writing.
The Core Pattern (Why? blurb)
[CREDENTIAL NOUN] [optional CONTEXT TAG] with [PROOF NOUNS]
Examples (real Sequoia recruiting feed shapes, swap the proof nouns to fit the subject):
- "Founding engineer with full-stack and AI infrastructure proven"
- "Founding engineer at ideal YC company with agentic expertise"
- "Princeton CS founding engineer with infrastructure and systems experience"
- "Bloomberg + AWS engineer with 0-to-1 shipping and full-stack capabilities"
Anatomy:
- Credential noun (lead):
Founding engineer,Princeton CS founding engineer,YC founding engineer,Bloomberg + AWS engineer,Agent infrastructure engineer. Strongest single noun phrase first. - Context tag (optional):
at YC AI company,at agent infrastructure startup. Only add when it sharpens the fit for the audience. - Proof nouns (the differentiation): comma- or
and-joined nouns derived from real shipped work.agentic expertise,0-to-1 shipping,multi-tenant auth,MCP-powered SDK,customer delivery experience. - Length: 10-22 words.
- Person: third-person fragment. No "I", no verb-led sentence.
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 · 163 lines · 156 tokens per session scan A 28e2de5a6182
voice is a skill published in the GitHub repository Kevin-Liu-01/Agent-Machines (29 stars, last pushed yesterday), licensed MIT. It adds 156 tokens to every session and 1,890 once invoked, about $0.0008 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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