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 metapelet-elder-checkingit 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/metapelet-elder-checkin)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/metapelet-elder-checkin"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/metapelet-elder-checkin/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/metapelet-elder-checkin"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/metapelet-elder-checkin.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 | $0.00056 | $0.00532 |
| Opus 5 | $0.00028 | $0.00266 |
| Sonnet 5 | $0.00011 | $0.00106 |
| Haiku 4.5 | $0.00006 | $0.00053 |
Grade A, and why
metapelet-elder-checkin 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 12d 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MetaPelet Elder Check-in
Use this skill when a caregiver or family member (with recipient consent) wants one friendly phone call to reduce loneliness between human visits — not a medical reminder and not a replacement for human care.
MetaPelet is an existing voice companion product; this skill packages its conversation rules for CALL-E outbound calls and a structured post-call summary.
When to use
- One outbound wellbeing check-in to a phone the elder already uses (landline or mobile).
- Conversation in Russian, Hebrew, or English (set in the request).
- Return structured results: mood, topics discussed, whether they want another call soon.
When not to use
- Medical reminders, triage, emergency response, or mental-health treatment.
- Unsolicited outreach or lead generation.
- Recurring schedules without a separate scheduler wrapper and explicit consent.
Workflow
- Read
references/safety.mdand confirm recipient consent. - Fill a request JSON with E.164
phone, explicit CALL-Eregionandlocale(seeapps/python/metapelet-checkin/example_request.json). - Preview (no call): run the Python app without
--execute. - Live call: set
CALLE_API_KEY, pass--execute --confirm-recipient-opt-in. - Share the redacted structured result with the authorized caregiver only.
Persona and profile
- Core persona:
references/persona.en.txt(MetaPelet companion snapshot, English repository text). - Optional demo profile shape:
references/profile-demo.en.txt. - Structured output schema:
references/result-schema.json.
Runnable app
The reference runner lives at apps/python/metapelet-checkin/ (relative to this submission repository root). It builds the CALL-E task text from the persona files and calls the CALL-E Python SDK when explicitly executed.
Output
After a completed call, expect JSON fields:
mood— short mood summarytopics— array of main topicswants_repeat_call—yes|no|unknown
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.
- 12d ago First seen · 52 lines · 56 tokens per session scan A cf65bffc2393
metapelet-elder-checkin is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (88 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 532 once invoked, about $0.0003 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.
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