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 nclamvn/openclawvn --skill eldercare-videocallgit clone --depth 1 https://github.com/nclamvn/openclawvnWrote 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/nclamvn/openclawvn/eldercare-videocall)<a href="https://agentmods.dev/skills/nclamvn/openclawvn/eldercare-videocall"><img src="https://agentmods.dev/badge/skills/nclamvn/openclawvn/eldercare-videocall/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/nclamvn/openclawvn/eldercare-videocall"><img src="https://agentmods.dev/badge/skills/nclamvn/openclawvn/eldercare-videocall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00114 | $0.01985 |
| Opus 5 | $0.00057 | $0.00992 |
| Sonnet 5 | $0.00023 | $0.00397 |
| Haiku 4.5 | $0.00011 | $0.00198 |
Grade A, and why
eldercare-videocall 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 11d 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Eldercare Video Call — Kết nối gia đình với bà
Tổng quan
Video call đi qua Zalo video call trực tiếp (KHÔNG dùng SIP/WebRTC/Twilio). OpenClaw đóng vai trò điều phối: kiểm tra bà sẵn sàng, chuẩn bị phòng, và hướng dẫn gia đình thời điểm gọi.
Tablet đặt cạnh giường bà chạy Zalo đăng nhập sẵn (tài khoản Zalo bà/ông). Fully Kiosk Browser giữ Zalo foreground, màn hình luôn sẵn sàng.
Flow A: Gia đình chủ động gọi bà (on-demand)
Bước 1: Nhận intent gọi bà
Gia đình nhắn vào Zalo group hoặc chat Bờm bot:
- "gọi bà", "gọi bà nội", "video call bà", "gọi cho bà", "muốn gọi bà"
Bước 2: Check trạng thái bà
Dùng tool home_assistant đọc sensors:
get_stateentitybinary_sensor.grandma_room_presence→ có người?get_stateentitysensor.grandma_room_motion_minutes→ phút từ cử động cuối
Quy tắc phân loại:
Bà ĐANG THỨC (motion < 15 phút): → Tiếp tục chuẩn bị phòng (Bước 3)
Bà có thể ĐANG NGỦ TRƯA (motion > 15 phút VÀ giờ 13:00-15:00): → Reply: "Bà có vẻ đang nghỉ trưa 😴 Gọi sau 15h nhé? Hay bạn muốn gọi ngay?" → Nếu gia đình reply "gọi ngay" / "gọi luôn" → tiếp tục Bước 3 → Nếu không reply → dừng
Bà ĐANG NGỦ ĐÊM (motion > 30 phút VÀ giờ 22:00-06:00): → Reply: "Bà đang ngủ rồi 🌙 Sáng mai gọi nhé?" → Chỉ tiếp tục nếu gia đình nói "khẩn cấp" / "gọi ngay"
Bà KHÔNG TRONG PHÒNG (presence = off): → Reply: "⚠️ Sensor không phát hiện người trong phòng bà. Kiểm tra lại nhé."
Bước 3: Chuẩn bị phòng bà
Nếu OK để gọi, dùng tool home_assistant thực hiện tuần tự:
3a. Bật đèn sáng vừa (không chói):
action: call_service
domain: light
service: turn_on
target_entity_id: light.grandma_room
service_data: { "brightness": 150, "color_temp_kelvin": 3000 }
3b. Tablet: Bật màn hình + mở Zalo:
Nếu có Fully Kiosk Browser REST API qua HA shell_command hoặc REST command:
action: call_service
domain: shell_command
service: tablet_screen_on
Hoặc ghi chú cho gia đình tự setup HA automation để bật tablet khi trigger.
What ships with it
1 file 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.
- 11d ago First seen · 223 lines · 114 tokens per session scan A 127329fa838a
eldercare-videocall is a skill published in the GitHub repository nclamvn/openclawvn (56 stars, last pushed 6mo ago), licensed MIT. It adds 114 tokens to every session and 1,985 once invoked, about $0.0006 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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