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-up)<a href="https://agentmods.dev/commands/cronusl-1141/ai-company/os-up"><img src="https://agentmods.dev/badge/commands/cronusl-1141/ai-company/os-up/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-up"><img src="https://agentmods.dev/badge/commands/cronusl-1141/ai-company/os-up.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 | $0.00014 | $0.00467 |
| Opus 5 | $0.00007 | $0.00234 |
| Sonnet 5 | $0.00003 | $0.00093 |
| Haiku 4.5 | $0.00001 | $0.00047 |
Grade A, and why
os-up scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s --max-time 2 http://localhost:8000/api/teams What it actually says
/os-up — 一键启动服务
启动 AI Team OS 的 API 服务器和 Dashboard 前端。
操作步骤
1. 检测API服务
curl -s --max-time 2 http://localhost:8000/api/teams
- 如果返回JSON → API已在运行，跳到步骤3
- 如果超时/失败 → 执行步骤2
2. 启动API服务（后台）
# 在项目根目录执行（即包含 pyproject.toml 的目录）
python -m uvicorn aiteam.api.app:create_app --host 0.0.0.0 --port 8000 --factory &
等待3秒后验证：
curl -s --max-time 3 http://localhost:8000/api/teams
3. 检测Dashboard
curl -s --max-time 2 http://localhost:5173
- 如果返回HTML → Dashboard已在运行，跳到步骤5
- 如果超时/失败 → 执行步骤4
4. 启动Dashboard（后台）
# 在项目的 dashboard 子目录执行
cd dashboard
npm run dev &
等待5秒后验证：
curl -s --max-time 3 http://localhost:5173
5. 报告状态
显示：
AI Team OS 服务状态:
- API: http://localhost:8000 ✅/❌
- Dashboard: http://localhost:5173 ✅/❌
- API文档: http://localhost:8000/docs
- WebSocket: ws://localhost:8000/ws
注意
- 使用后台方式启动（
&），不阻塞当前会话 - 启动前检测避免重复启动
- Dashboard使用npm run dev（开发模式），关闭时用Ctrl+C或'q'
- 如果启动失败，提示检查依赖：
pip install -e ".[all]"和cd dashboard && npm install
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 · 63 lines · 14 tokens per session scan A c0222d7e223d
os-up is a command published in the GitHub repository CronusL-1141/AI-company (357 stars, last pushed 2d ago), licensed MIT. It adds 14 tokens to every session and 467 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
agent-brain-graph
Search using GraphRAG for relationship and dependency queries.
tools
Manage MCP tools with natural language commands to list, enable, and disable tools and tool groups.
q-research
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.
create-pr
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.
r-util-proj-cross
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.