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 CALLE-AI/awesome-phone-call-agents --skill rdn-intake-referralgit clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agentsWrote 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/calle-ai/awesome-phone-call-agents/rdn-intake-referral)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/rdn-intake-referral"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/rdn-intake-referral/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/calle-ai/awesome-phone-call-agents/rdn-intake-referral"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/rdn-intake-referral.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 | $0.00034 | $0.01491 |
| Opus 5 | $0.00017 | $0.00745 |
| Sonnet 5 | $0.00007 | $0.00298 |
| Haiku 4.5 | $0.00003 | $0.00149 |
Grade A, and why
rdn-intake-referral 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 8d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RDN Intake & Referral
Purpose
Use this skill to conduct a short, consent-based phone conversation with a patient seeking nutrition support and produce a structured intake summary for review by a Registered Dietitian Nutritionist (RDN).
The skill is for intake and care coordination only. It does not diagnose medical conditions, prescribe treatment, or provide personalized medical or nutrition advice.
Required Inputs
Before starting a live call, the workflow must have:
- The patient's phone number in E.164 format.
- Authorization to contact the patient for nutrition intake.
- The purpose of the call: nutrition support intake and possible RDN referral.
- Any available referral context supplied by the authorized caller or workflow.
- A clear indication that the patient should be informed they are speaking with an AI assistant.
Do not invent or infer a phone number, patient information, referral information, or insurance information.
Preflight
Before any live call:
- Verify that the phone number is present and formatted in E.164 format.
- Verify that the calling purpose is nutrition intake and possible RDN referral.
- Verify that the caller has authorization to contact the patient.
- Confirm that no API key, credential, or authentication token is included in the call input.
- Confirm that the workflow is ready to return a structured intake result.
- If any required preflight condition fails, do not place the call and return
needs_human.
Never guess missing information during preflight.
Dry-Run Preview
Before a live call, generate a preview containing:
- The masked destination phone number.
- The purpose of the call.
- The information the agent intends to collect.
- The expected structured result fields.
- Any available referral context.
The preview must not place a phone call.
A live call may proceed only after the required authorization and confirmation conditions have been satisfied.
CALL-E Goal Template
Use the following goal when planning the phone call:
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.
- 8d ago First seen · 158 lines · 34 tokens per session scan A 196b28f8a99d
rdn-intake-referral is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (88 stars, last pushed yesterday), licensed MIT. It adds 34 tokens to every session and 1,491 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 2026-09-03.
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