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.
git clone --depth 1 https://github.com/CronusL-1141/AI-companyWrote 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/commands/cronusl-1141/ai-company/os-init)<a href="https://agentmods.dev/commands/cronusl-1141/ai-company/os-init"><img src="https://agentmods.dev/badge/commands/cronusl-1141/ai-company/os-init/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/commands/cronusl-1141/ai-company/os-init"><img src="https://agentmods.dev/badge/commands/cronusl-1141/ai-company/os-init.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 | $0.00016 | $0.00384 |
| Opus 5 | $0.00008 | $0.00192 |
| Sonnet 5 | $0.00003 | $0.00077 |
| Haiku 4.5 | $0.00002 | $0.00038 |
Grade A, and why
os-init 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 10d 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
/os-init — 系统初始化
你需要帮助用户初始化 AI Team OS 项目配置。
操作步骤
- 检查当前目录是否已有
aiteam.yaml配置文件 - 如果已存在，询问用户是否需要重新初始化
- 向用户展示可用模板并让其选择：
- research — 研究团队模板（首席研究员 + 文献分析师 + 数据分析师）
- development — 开发团队模板（技术总监 + 后端开发 + 前端开发 + 测试工程师）
- analysis — 分析团队模板（首席分析师 + 数据采集员 + 数据建模师）
- 默认 — 空白配置，手动编辑
- 使用 Bash 工具执行初始化命令：
或不带模板参数生成默认配置python -m aiteam.cli.app init --template <template> - 展示初始化结果和后续步骤
初始化后提示
初始化完成后，告知用户后续步骤：
## 初始化完成
已生成配置文件: aiteam.yaml
已创建工作目录: .aiteam/
### 后续步骤
1. 编辑 `aiteam.yaml` 自定义团队配置
2. 运行 `/os-up` 启动 API 服务
3. 运行 `/os-status` 查看系统状态
4. 运行 `/os-help` 查看更多可用命令
注意
- 所有输出使用中文
- 如果配置文件已存在，必须先征得用户同意才能覆盖
- 初始化不会启动服务，仅创建配置文件
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.
- 10d ago First seen · 48 lines · 16 tokens per session scan A debd0692e8c3
os-init is a command published in the GitHub repository CronusL-1141/AI-company (357 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 384 once invoked, about $0.0001 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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Read the research-mode skill's SKILL.md for the full ruleset before proceeding. Follow all constraints, the source lookup cascade, the token budget, and the "what counts as cited" rules exactly.
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Push the current branch and open a pull request into main with a structured description derived from the branch's commits and the open issues it resolves.
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Cross-project analysis for workspace project sets. Reads MEMORY.md, PLAN.md, AUDIT.md, and CLAUDE.md from all projects to identify shared patterns, duplicate effort, convention drift, and alignment opportunities.
forge-docs
Generate or review documentation for the specified file or module.