Borrowing it
Nothing to install: this file belongs to znlnzi/claude-config-studio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/znlnzi/claude-config-studio/main/.claude/skills/team/SKILL.mdgit clone --depth 1 https://github.com/znlnzi/claude-config-studioWrote 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/znlnzi/claude-config-studio/team)<a href="https://agentmods.dev/skills/znlnzi/claude-config-studio/team"><img src="https://agentmods.dev/badge/skills/znlnzi/claude-config-studio/team/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/znlnzi/claude-config-studio/team"><img src="https://agentmods.dev/badge/skills/znlnzi/claude-config-studio/team.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 | $0.00035 | $0.00569 |
| Opus 5.5 | $0.00014 | $0.00228 |
| Sonnet 5.5 | $0.00007 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
team 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.
What it actually says
组建临时团队
根据任务，从公司现有 AI Agent 中挑选最合适的成员，组建临时团队协作完成。
可用 Agent
| Agent | 文件 | 职能 |
|---|---|---|
| CEO | ceo-bezos | 战略决策、商业模式、PR/FAQ、优先级 |
| CTO | cto-vogels | 技术架构、技术选型、系统设计 |
| 产品设计 | product-norman | 产品定义、用户体验、可用性 |
| UI 设计 | ui-duarte | 视觉设计、设计系统、配色排版 |
| 交互设计 | interaction-cooper | 用户流程、Persona、交互模式 |
| 全栈开发 | fullstack-dhh | 代码实现、技术方案、开发 |
| QA | qa-bach | 测试策略、质量把控、Bug 分析 |
| 营销 | marketing-godin | 定位、品牌、获客、内容 |
| 运营 | operations-pg | 用户运营、增长、社区、PMF |
| 销售 | sales-ross | 定价、销售漏斗、转化 |
执行步骤
1. 分析任务，选择成员
根据任务性质，选择 2-5 个最相关的 Agent。选人原则：
- 只选必要的：精准匹配任务需求
- 考虑协作链：确保链路上的关键角色都在
- 避免冗余：职能重叠的不要同时选
2. 组建 Agent Team
使用 Agent Teams 功能组建临时团队：
- 创建团队，team_name 基于任务简短命名
- 为每个成员创建具体任务
- 用 Task 工具 spawn 每个 teammate
3. 协调与汇总
- 作为 team lead 协调各成员工作
- 收集各成员产出，汇总为统一方案
- 如有分歧，列出各方观点供创始人决策
- 完成后清理团队资源
注意事项
- 所有沟通使用中文，技术术语保留英文
- 每个成员产出的文档存放在 docs// 下
- 团队是临时的，任务完成后即解散
- 创始人是最终决策者
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 · 51 lines · 35 tokens per session scan A 07a4e67a092a
team is a skill published in the GitHub repository znlnzi/claude-config-studio (0 stars, last pushed 8mo ago), licensed MIT. It adds 35 tokens to every session and 569 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 2026-08-31.
Other skills, from other repositories
opencli-usage
Discover and invoke OpenCLI capabilities for websites and Chrome. Find commands, inspect schemas, interpret results and choose browser or adapter tools.
crit-story
Author a crit story and continue the interactive review loop only when the user explicitly invokes crit-story or directly asks you to generate a crit story. Do not infer this skill from generic review, PR, or diff-review requests.
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
mnemon
Persistent memory for MiniMax Code. Recall durable context, store important facts and decisions, and link related memories with the mnemon CLI.
tokf-filter
This skill should be used when the user asks to "create a filter", "write a tokf filter", "add a filter for ", "how do I filter output", or needs guidance on tokf filter step types, templates, pipes, or placement conventions.
tokf-discover
Find missed token savings by scanning AI coding session files for commands that ran without tokf filtering.