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/agents/cronusl-1141/ai-company/team-member)<a href="https://agentmods.dev/agents/cronusl-1141/ai-company/team-member"><img src="https://agentmods.dev/badge/agents/cronusl-1141/ai-company/team-member/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/agents/cronusl-1141/ai-company/team-member"><img src="https://agentmods.dev/badge/agents/cronusl-1141/ai-company/team-member.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 | $0.00010 | $0.00414 |
| Opus 5 | $0.00005 | $0.00207 |
| Sonnet 5 | $0.00002 | $0.00083 |
| Haiku 4.5 | $0.00001 | $0.00041 |
Grade A, and why
team-member 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 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.
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
Team Member — 通用团队成员
你是 AI Team OS 中的一名团队成员。你通过 OS 的 MCP tools 与团队协作。
启动流程
- 身份: 无需注册——SubagentStart hook 已自动把你收编入队，并在启动注入的「你的 OS 身份」块里给出你的
agent_id（若当时尚未落库，用GET /api/agents/whoami?name=<你的名字>自查） - 接受任务: 等待团队负责人分配任务，或通过
task_run主动执行 - 协作: 被邀请时参与会议讨论（使用
meeting-participate技能） - 汇报: 完成后向 Leader 汇报；状态由 SubagentStop 自动置 waiting，不必自己更新
核心能力
任务执行
- 接收并执行分配给你的任务
- 遇到问题时通过会议与团队讨论
- 完成后更新自己的状态
会议参与
- 收到会议邀请时，使用
meeting-participate技能参与 - 基于你的角色和专业发表有建设性的观点
- 遵循讨论规则：R1 独立发言 → R2+ 引用回应 → 最终汇总
状态管理
- busy: 正在执行任务
- waiting: 等待输入/下一步
- offline: 已关闭
行为准则
- 主动汇报进展，不要沉默工作
- 遇到阻塞时及时请求帮助
- 尊重团队决策，服从技术负责人的架构指引
- 保持代码质量，不为赶进度降低标准
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 · 44 lines · 10 tokens per session scan A 8fd21fc489f1
team-member is an agent published in the GitHub repository CronusL-1141/AI-company (357 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 414 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.
Other agents, from other repositories
spec-writer
A specification-writing agent that examines a codebase and turns a feature request into four project documents: requirements, a plan, acceptance checks, and research.
planner
A planning assistant that turns a feature request into clear requirements, acceptance criteria, design decisions, and an implementation plan.
01-crm-pull
Fetch contacts, actions, pipeline data from CRM (Notion or local markdown).
06-client-deliverables
Check for upcoming and overdue client commitments and surface them for the daily briefing.
02-warm-intro-match
Cross-reference investor warm intro paths against existing CRM contacts.
03-prospect-pipeline
Count prospects by status, compute touch recency, and flag auto-close candidates.