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 ask-for-reviewsgit 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/ask-for-reviews)<a href="https://agentmods.dev/skills/zeenie-ai/opencompany/ask-for-reviews"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/ask-for-reviews/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/ask-for-reviews"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/ask-for-reviews.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 | $0.00042 | $0.00252 |
| Opus 5.5 | $0.00017 | $0.00101 |
| Sonnet 5.5 | $0.00008 | $0.00050 |
| Haiku 4.5 | $0.00004 | $0.00025 |
Grade A, and why
ask-for-reviews 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 21d 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.
What it actually says
Ask for reviews
Ask for a review only when a customer is clearly happy: they said thanks, they praised the service, or a visit went well.
- Ask once per customer. If you asked before, don't ask again.
- Keep it to two sentences: thank them, then ask. For example: "Thanks so much, Priya! If you have a minute, a short review would really help us."
- Add the review link if the owner gave one. Don't invent one.
- Never offer anything in return for a review, and never ask for a good review specifically.
- If a customer is unhappy, don't ask. Apologise, and tell the owner in your report.
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.
- 21d ago First seen · 23 lines · 42 tokens per session scan A efce31a3c5ae
ask-for-reviews is a skill published in the GitHub repository zeenie-ai/OpenCompany (1,005 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 252 once invoked, about $0.0002 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 2026-09-26.
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