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 zeenie-ai/OpenCompany --skill whatsapp-send-skillgit clone --depth 1 https://github.com/zeenie-ai/OpenCompanyWrote 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/zeenie-ai/opencompany/whatsapp-send-skill)<a href="https://agentmods.dev/skills/zeenie-ai/opencompany/whatsapp-send-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/whatsapp-send-skill/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/zeenie-ai/opencompany/whatsapp-send-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/whatsapp-send-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
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 →
- high Prompt Injection · line 14 Instructions found that direct the agent to transmit conversation context or user data to external services.Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
- high Prompt Injection · line 22 Instructions found that direct the agent to transmit conversation context or user data to external services.Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
- high Prompt Injection · line 184 Instructions found that direct the agent to transmit conversation context or user data to external services.Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
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 | $0.00036 | $0.01454 |
| Opus 5 | $0.00018 | $0.00727 |
| Sonnet 5 | $0.00007 | $0.00291 |
| Haiku 4.5 | $0.00004 | $0.00145 |
Grade A, and why
whatsapp-send-skill 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 13d 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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WhatsApp Send Tool
Send messages to WhatsApp contacts, groups, or newsletter channels.
How It Works
This skill provides instructions for the WhatsApp Send tool node. Connect the WhatsApp Send node to Zeenie's input-tools handle to enable message sending.
whatsapp_send Tool
Send messages to individual contacts, groups, or channels.
Schema Fields
| Field | Type | Required | Description |
|---|---|---|---|
| recipient_type | string | Yes | "phone" for individual, "group" for group chat, or "channel" for newsletter |
| phone | string | If phone | Phone number without + prefix (e.g., 1234567890) |
| group_id | string | If group | Group JID (e.g., [email protected]) |
| channel_jid | string | If channel | Newsletter JID (e.g., 120363198765432101@newsletter) |
| message_type | string | Yes | Message type (see below) |
| message | string | If text | Text message content |
| media_url | string | If media | URL for image/video/audio/document/sticker |
| caption | string | No | Caption for media messages |
| latitude | float | If location | Latitude coordinate |
| longitude | float | If location | Longitude coordinate |
| location_name | string | No | Display name for location |
| address | string | No | Address text for location |
| contact_name | string | If contact | Contact display name |
| vcard | string | If contact | vCard 3.0 format string |
Message Types
| Type | Required Fields | Description |
|---|---|---|
text |
message | Plain text message |
image |
media_url | Image file (JPG, PNG, GIF) |
video |
media_url | Video file (MP4) |
audio |
media_url | Audio file (MP3, OGG, WAV) |
document |
media_url | Any file type |
sticker |
media_url | Sticker image (WebP) |
location |
latitude, longitude | GPS coordinates |
contact |
contact_name, vcard | Contact card |
Examples
Send text message to contact:
{
"recipient_type": "phone",
"phone": "1234567890",
"message_type": "text",
"message": "Hello! How are you?"
}
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.
- 13d ago First seen · 194 lines · 36 tokens per session scan A a4f97b831120
whatsapp-send-skill is a skill published in the GitHub repository zeenie-ai/OpenCompany (883 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 1,454 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 2026-08-30.
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