OpenCompany is an application for creating AI employees that work on assigned jobs in the background on the user's computer, using teams of specialized agents coordinated by a lead agent. People connect these employees to tools such as email, calendars, messages, and code, then define their workflows through a visual editor.
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 google-gmail-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/google-gmail-skill)<a href="https://agentmods.dev/skills/zeenie-ai/opencompany/google-gmail-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/google-gmail-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/google-gmail-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/google-gmail-skill.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 | $0.00030 | $0.00934 |
| Opus 5.5 | $0.00012 | $0.00374 |
| Sonnet 5.5 | $0.00006 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
google-gmail-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 2mo 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gmail Skill
Send, search, and read emails using Gmail API.
Tool: google_gmail
Consolidated Gmail tool with operation parameter.
Operations
| Operation | Description | Required Fields |
|---|---|---|
send |
Send an email | to, subject, body |
search |
Search emails by query | query |
read |
Read email by ID | message_id |
send - Send an email
| Field | Type | Required | Description |
|---|---|---|---|
| operation | string | Yes | Must be "send" |
| to | string | Yes | Recipient email address |
| subject | string | Yes | Email subject line |
| body | string | Yes | Email body (plain text or HTML) |
| cc | string | No | CC recipients (comma-separated) |
| bcc | string | No | BCC recipients (comma-separated) |
| body_type | string | No | "text" or "html" (default: text) |
Example - Send plain text email:
{
"operation": "send",
"to": "[email protected]",
"subject": "Meeting Tomorrow",
"body": "Hi,\n\nJust a reminder about our meeting tomorrow at 2pm.\n\nBest regards"
}
Example - Send HTML email:
{
"operation": "send",
"to": "[email protected]",
"subject": "Weekly Report",
"body": "<h1>Weekly Report</h1><p>Here are the highlights...</p>",
"body_type": "html"
}
search - Search emails
| Field | Type | Required | Description |
|---|---|---|---|
| operation | string | Yes | Must be "search" |
| query | string | Yes | Gmail search query |
| max_results | integer | No | Maximum results (default: 10, max: 100) |
| include_body | boolean | No | Fetch full message body (default: false) |
Query Syntax Examples:
from:[email protected]- Emails from specific senderto:[email protected]- Emails to specific recipientsubject:meeting- Emails with "meeting" in subjecthas:attachment- Emails with attachmentsis:unread- Unread emailsafter:2024/01/01- Emails after datebefore:2024/12/31- Emails before datelabel:important- Emails with label"exact phrase"- Exact phrase matchfrom:[email protected] is:unread- Combine multiple filters
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.
- 2mo ago First seen · 119 lines · 30 tokens per session scan A 5ff7b3ea8282
google-gmail-skill is a skill published in the GitHub repository zeenie-ai/OpenCompany (1,045 stars, last pushed 5d ago), licensed MIT. It adds 30 tokens to every session and 934 once invoked, about $0.0001 per session on Opus 5.5. 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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