Borrowing it
Nothing to install: this file belongs to Enriquemarq1/zernio-library-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Enriquemarq1/zernio-library-skills/main/.claude/skills/zernio-voice-agent/SKILL.mdgit clone --depth 1 https://github.com/Enriquemarq1/zernio-library-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/enriquemarq1/zernio-library-skills/zernio-voice-agent)<a href="https://agentmods.dev/skills/enriquemarq1/zernio-library-skills/zernio-voice-agent"><img src="https://agentmods.dev/badge/skills/enriquemarq1/zernio-library-skills/zernio-voice-agent/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/enriquemarq1/zernio-library-skills/zernio-voice-agent"><img src="https://agentmods.dev/badge/skills/enriquemarq1/zernio-library-skills/zernio-voice-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 75 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00161 | $0.02192 |
| Opus 5.5 | $0.00064 | $0.00877 |
| Sonnet 5.5 | $0.00032 | $0.00438 |
| Haiku 4.5 | $0.00016 | $0.00219 |
Grade A, and why
zernio-voice-agent 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.
curl -s -X POST "https://zernio.com/api/v1/whatsapp/phone-numbers/{phoneNumberDocId}/calling" \ How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
zernio-voice-agent
One WhatsApp number, full AI front desk. Text it → an AI answers in chat. Call it → an AI voice picks up. Two tools, one bridge:
- Zernio owns the WhatsApp number: the text workflow (chat brain) and the call routing.
- Retell AI is the voice: real-time listen → think → talk, human-sounding.
- The bridge is one field: the number's
forwardTo→ your Retell agent's SIP/wss endpoint.
The skill informs; the agent acts. This file +
reference/give Claude the verified contract. You stay in control — Claude shows you both prompts, the graph, and the calling config before creating or activating anything (it goes live on a real business number).
The architecture (live-proven shape)
ONE WhatsApp NUMBER (Zernio, calling-eligible)
/ \
TEXT: inbound message CALL: inbound WhatsApp call
│ │
Zernio workflow: tag → human-escape → ai (memory) → reply → wait │ number's calling config:
│ contact asks to TALK │ forwardTo: sip:<retell>@sip.retellai.com
└─▶ send TAP-TO-CALL deep link (wa.me/call/<number>) ────────┤
▼
Retell voice agent ANSWERS
(same persona as the text agent)
Why tap-to-call instead of the outbound start_call node: outbound calling is gated
separately by Meta (outboundDisabled stays true on most numbers). The deep link needs only
INBOUND calling, works the moment forwardTo is set, and converts better anyway — the contact
chooses to call. Keep start_call for when outbound unlocks.
What Claude needs (ask once, remember in-session)
- ZERNIO_API_KEY + RETELL_API_KEY (Retell needs a card on file to provision a number).
- profileId + accountId of the WhatsApp account (
GET /v1/profiles,GET /v1/accounts). - A calling-eligible WhatsApp number — see the gates below. This is the long pole.
- The business details in plain words — for BOTH prompts (text + voice), same persona.
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 · 134 lines · 161 tokens per session scan A 9c297775182f
zernio-voice-agent is a skill published in the GitHub repository Enriquemarq1/zernio-library-skills (49 stars, last pushed 3d ago), licensed MIT. It adds 161 tokens to every session and 2,192 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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