{"id":"385d7921-0ea6-4c16-9c59-ad6fa5e48012","entityType":"agent","slug":"sunnyeung369-ai-agent-team","name":"ai-agent-team","canonicalUrl":"https://www.xpersona.co/agent/sunnyeung369-ai-agent-team","canonicalPath":"/agent/sunnyeung369-ai-agent-team","generatedAt":"2026-10-09T19:20:32.753Z","source":"GITHUB_OPENCLEW","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-04-15T05:21:22.124Z","emptyReason":null},"description":"AI Agent 协作团队系统 - 基于 newtype-profile 架构。模拟编辑团队模型，通过多个专业 Agent 协作完成复杂任务。适用于内容创作、研究分析、知识管理等场景。核心 Agent: chief(主编/协调者), researcher(研究员), writer(作者), editor(编辑), fact-checker(核查员), archivist(档案员)。支持任务分类、并行处理、质量验证等高级协作模式。触发词: 'agent team', '协作', '研究分析', '内容创作', '多角度分析' --- name: ai-agent-team version: \"1.0.0\" description: \"AI Agent 协作团队系统 - 基于 newtype-profile 架构。模拟编辑团队模型，通过多个专业 Agent 协作完成复杂任务。适用于内容创作、研究分析、知识管理等场景。核心 Agent: chief(主编/协调者), researcher(研究员), writer(作者), editor(编辑), fact-checker(核查员), archivist(档案员)。支持任务分类、并行处理、质量验证等高级协作模式。触发词: 'agent team', '协作', '研究分析', '内容创作', '多角度分析'\" user-invocable: true --- AI Agent Team SKILL 概述 基于 $1 架构的 AI Agent 协作系统，将复杂任务分配给专业化的 Agent 团队协作完成。","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. 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基于 newtype-profile 架构。模拟编辑团队模型，通过多个专业 Agent 协作完成复杂任务。适用于内容创作、研究分析、知识管理等场景。核心 Agent: chief(主编/协调者), researcher(研究员), writer(作者), editor(编辑), fact-checker(核查员), archivist(档案员)。支持任务分类、并行处理、质量验证等高级协作模式。触发词: 'agent team', '协作', '研究分析', '内容创作', '多角度分析'\"\nuser-invocable: true\n---\n\n# AI Agent Team SKILL\n\n## 概述\n\n基于 [newtype-profile](https://github.com/newtype-01/newtype-profile) 架构的 AI Agent 协作系统，将复杂任务分配给专业化的 Agent 团队协作完成。\n\n## 核心理念\n\n采用**编辑团队模型**，每个 Agent 扮演特定角色，通过协作完成单 Agent 难以处理的复杂任务。\n\n## Agent 团队\n\n### 🎯 Chief (主编/任务协调者)\n\n**角色定位**: 探索伙伴 + 任务协调者（双模式）\n\n**职责**:\n- 理解用户意图和需求\n- 将复杂任务分解为子任务\n- 协调其他 Agent 的工作\n- 整合各 Agent 的输出\n- 质量控制和最终审核\n\n**使用场景**:\n- 复杂任务的初始规划\n- 多步骤任务的流程设计\n- Agent 之间的协调和调度\n- 最终输出的整合和优化\n\n**调用方式**:\n```\n[Chief] 请帮我规划这个内容创作项目的完整流程\n```\n\n---\n\n### 🔍 Researcher (研究员/信息收集者)\n\n**角色定位**: 情报员，广泛搜索和发现新信息\n\n**职责**:\n- 进行背景研究\n- 收集相关资料和数据\n- 发现最新的趋势和动态\n- 提供多角度的信息来源\n\n**使用场景**:\n- 需要深入了解某个主题\n- 收集行业趋势和最新发展\n- 寻找案例和参考材料\n- 探索不同观点和见解\n\n**调用方式**:\n```\n[@researcher] 研究一下 AI 在 2024 年的发展趋势\n```\n\n---\n\n### ✍️ Writer (作者/内容创作者)\n\n**角色定位**: 内容生产者，负责起草和创作\n\n**职责**:\n- 基于研究结果创作内容\n- 采用适当的写作风格和语调\n- 确保内容流畅和可读性\n- 符合目标受众的需求\n\n**使用场景**:\n- 撰写文章、报告、文档\n- 创作营销文案\n- 编写技术教程\n- 生成创意内容\n\n**调用方式**:\n```\n[@writer] 基于研究结果，撰写一篇关于 AI 趋势的文章\n```\n\n---\n\n### 📝 Editor (编辑/内容精炼者)\n\n**角色定位**: 内容优化者，提升内容质量\n\n**职责**:\n- 审查和精炼内容\n- 优化结构和逻辑\n- 改善语言表达\n- 确保一致性和准确性\n\n**使用场景**:\n- 审查初稿并提供反馈\n- 优化段落结构和逻辑流\n- 提升语言表达和文风\n- 确保内容符合规范\n\n**调用方式**:\n```\n[@editor] 审查并优化这篇文章的结构和表达\n```\n\n---\n\n### ✅ Fact-Checker (核查员/信息验证者)\n\n**角色定位**: 信息验证者，确保内容准确性\n\n**职责**:\n- 验证事实和数据的准确性\n- 检查引用和来源的可信度\n- 识别可能的问题和争议\n- 提供客观的评估\n\n**使用场景**:\n- 验证统计数据和事实陈述\n- 检查引用来源的可靠性\n- 识别潜在的偏见或误导\n- 确保内容的准确性\n\n**调用方式**:\n```\n[@fact-checker] 验证文章中提到的数据和事实\n```\n\n---\n\n### 📚 Archivist (档案员/知识管理者)\n\n**角色定位**: 知识库管理者，建立信息和发现关联\n\n**职责**:\n- 检索相关知识和文档\n- 建立信息之间的关联\n- 提供历史参考和案例\n- 组织和管理知识库\n\n**使用场景**:\n- 查找相关的历史文档\n- 建立知识点之间的联系\n- 提供过往案例和参考\n- 组织项目知识库\n\n**调用方式**:\n```\n[@archivist] 查找我们之前关于类似主题的文档\n```\n\n---\n\n## 任务分类系统\n\n基于任务类型自动选择合适的 Agent：\n\n| 任务类别 | 主要 Agent | 辅助 Agent | 典型场景 |\n|---------|-----------|-----------|---------|\n| **research** | researcher | archivist | 信息研究、趋势发现、背景调查 |\n| **writing** | writer | researcher, editor | 内容创作、文章撰写、文案生成 |\n| **editing** | editor | fact-checker | 内容精炼、结构优化、质量提升 |\n| **fact-check** | fact-checker | researcher | 事实验证、来源核查、可信度评估 |\n| **archive** | archivist | researcher | 知识检索、文档查找、关联建立 |\n| **planning** | chief | 所有 Agent | 项目规划、任务分解、流程设计 |\n| **review** | chief + editor | fact-checker | 全面审查、质量把控、最终审核 |\n| **quick** | 任意单个 Agent | 无 | 简单快速任务，单一 Agent 即可 |\n\n---\n\n## 典型工作流程\n\n### 1. 内容创作流程\n\n```\n[Chief] 接收需求 → 分解任务\n    ↓\n[@researcher] 研究主题，收集信息\n    ↓\n[@writer] 基于研究结果创作内容\n    ↓\n[@editor] 审查并优化内容\n    ↓\n[@fact-checker] 验证事实和数据\n    ↓\n[Chief] 最终审核并整合输出\n```\n\n### 2. 研究分析流程\n\n```\n[Chief] 定义研究目标\n    ↓\n[@researcher] 进行初步研究\n    ↓\n[@archivist] 建立知识关联，查找历史资料\n    ↓\n[@fact-checker] 验证关键信息\n    ↓\n[@writer] 撰写研究报告\n    ↓\n[@editor] 优化报告结构\n    ↓\n[Chief] 整合并输出最终分析\n```\n\n### 3. 知识管理流程\n\n```\n[Chief] 确定知识管理目标\n    ↓\n[@archivist] 检索相关文档\n    ↓\n[@researcher] 补充最新信息\n    ↓\n[@fact-checker] 验证内容准确性\n    ↓\n[@editor] 整理和优化知识结构\n    ↓\n[Chief] 建立知识索引和关联\n```\n\n---\n\n## 使用指南\n\n### 基本用法\n\n#### 方式一：指定特定 Agent\n\n```\n# 请研究员进行背景调查\n[@researcher] 研究一下微服务架构的最新趋势\n\n# 请作者撰写内容\n[@writer] 基于研究结果，撰写一篇技术文章\n\n# 请编辑优化内容\n[@editor] 审查并优化这篇文章\n```\n\n#### 方式二：让主编自动协调\n\n```\n# 完整的内容创作任务\n[Chief] 我需要创作一篇关于 AI Agent 的深度文章\n      请安排团队协作完成\n\n# 复杂的研究分析任务\n[Chief] 帮我分析一下区块链技术在供应链中的应用前景\n      请团队协作进行深入研究\n```\n\n#### 方式三：使用任务分类\n\n```\n# 研究任务\n[task:research] 调查量子计算的发展现状\n\n# 写作任务\n[task:writing] 撰写一份产品发布新闻稿\n\n# 编辑任务\n[task:editing] 优化这份技术文档的结构和表达\n\n# 核查任务\n[task:fact-check] 验证报告中的所有统计数据\n```\n\n---\n\n## 高级功能\n\n### 1. 并行处理\n\n对于可以并行执行的独立任务，Chief 会协调多个 Agent 同时工作：\n\n```\n[Chief] 我需要：\n      - 研究市场趋势（researcher）\n      - 分析竞品情况（archivist）\n      - 收集用户反馈（researcher）\n      请协调团队并行完成这些任务\n```\n\n### 2. 迭代优化\n\n支持多轮迭代，持续改进内容质量：\n\n```\n[Chief] 启动迭代优化流程\n      第一轮：writer 起草\n      第二轮：editor 优化\n      第三轮：fact-checker 验证\n      直到达到质量标准\n```\n\n### 3. 质量检查点\n\n在关键节点设置质量检查：\n\n```\n[Chief] 设置质量检查点：\n      - 研究阶段：确保信息全面\n      - 写作阶段：确保内容完整\n      - 编辑阶段：确保结构清晰\n      - 最终阶段：确保准确无误\n```\n\n### 4. Agent 投票机制\n\n对于争议性问题，可以采用多 Agent 投票：\n\n```\n[Chief] 这个技术方案有争议\n      请 researcher, archivist, fact-checker\n      分别评估并提供意见\n      综合分析后做出决策\n```\n\n---\n\n## 最佳实践\n\n### ✅ DO (推荐做法)\n\n1. **明确任务目标**\n   - 清楚地说明你想要达成的目标\n   - 提供足够的背景和上下文\n\n2. **合理选择 Agent**\n   - 简单任务使用单个 Agent\n   - 复杂任务让 Chief 协调团队\n   - 使用任务分类自动选择\n\n3. **遵循工作流程**\n   - 研究先行（researcher → writer）\n   - 验证在后（fact-checker 辅助）\n   - 迭代优化（多轮 editor）\n\n4. **提供具体反馈**\n   - 对 Agent 的输出提供反馈\n   - 明确指出需要改进的地方\n\n### ❌ DON'T (避免做法)\n\n1. 不要跳过研究直接创作（缺乏深度）\n2. 不要忽略事实核查（可能出错）\n3. 不要省略编辑环节（质量不佳）\n4. 不要对简单任务使用全部 Agent（效率低）\n\n---\n\n## 示例场景\n\n### 场景 1: 撰写技术博客\n\n```\n用户: [Chief] 我需要写一篇关于 RAG 技术的技术博客\n\nChief: 好的，我将协调团队完成：\n\n1. [@researcher] 研究 RAG 技术的原理、应用场景、最新进展\n2. [@archivist] 查找我们之前的相关文档和案例\n3. [@writer] 基于研究结果撰写技术博客\n4. [@editor] 审查并优化技术内容和表达\n5. [@fact-checker] 验证技术细节和数据\n6. [Chief] 最终审核并整合输出\n\n预计时间线：研究 → 起草 → 编辑 → 核查 → 定稿\n```\n\n### 场景 2: 市场分析报告\n\n```\n用户: [Chief] 分析 AI Agent 市场的发展前景\n\nChief: 我将组织团队进行全面分析：\n\n1. [@researcher] 调研市场规模、增长趋势、主要玩家\n2. [@archivist] 收集历史数据和过往案例\n3. [@fact-checker] 验证市场数据和预测\n4. [@writer] 撰写分析报告\n5. [@editor] 优化报告结构和逻辑\n6. [Chief] 整合并提供最终洞察\n\n输出：完整的市场分析报告 + 关键发现 + 发展建议\n```\n\n### 场景 3: 知识库构建\n\n```\n用户: [Chief] 帮我构建一个云原生技术知识库\n\nChief: 我将协调知识管理团队：\n\n1. [@archivist] 设计知识库结构和分类体系\n2. [@researcher] 收集各个技术领域的核心知识\n3. [@fact-checker] 验证技术概念的准确性\n4. [@editor] 整理和优化知识条目\n5. [@archivist] 建立知识点之间的关联\n6. [Chief] 建立索引和检索系统\n\n输出：结构化知识库 + 知识图谱 + 检索系统\n```\n\n---\n\n## 与其他 SKILL 的协作\n\n### 推荐组合\n\n1. **+ planning-with-files**\n   - 先用 planning-with-files 制定项目计划\n   - 再用 ai-agent-team 执行具体任务\n\n2. **+ content-research-writer**\n   - 使用 content-research-writer 的研究能力\n   - 配合 ai-agent-team 的协作模式\n\n3. **+ obsidian-markdown**\n   - 用 ai-agent-team 创作内容\n   - 用 obsidian-markdown 格式化输出\n\n4. **+ pdf/xlsx/docx**\n   - Agent 团队完成内容创作\n   - 输出为各种格式的文档\n\n---\n\n## 配置和自定义\n\n### 自定义 Agent 角色\n\n你可以根据项目需求自定义 Agent 的角色和职责：\n\n```\n示例：添加专门的代码审查 Agent\n\n[@code-reviewer] 专门负责代码质量审查\n- 遵循最佳实践\n- 检查安全性问题\n- 优化性能和可维护性\n```\n\n### 自定义工作流程\n\n根据你的具体需求调整工作流程：\n\n```\n示例：快速内容生产流程\n\n1. [Chief] 快速任务分解\n2. [@researcher] 并行收集信息（30分钟）\n3. [@writer] 快速起草（1小时）\n4. [@editor] 简要优化（30分钟）\n5. [Chief] 快速审核并输出\n\n总时长：约 2-3 小时\n```\n\n---\n\n## 限制和注意事项\n\n1. **模型限制**\n   - 所有 Agent 共用同一个底层模型（Claude Sonnet 4.5）\n   - 不支持 newtype-profile 的多模型切换（需要手动模拟）\n\n2. **并发限制**\n   - 实际上是串行调用各 Agent 的能力\n   - 不是真正的并行执行（但逻辑上可以并行）\n\n3. **上下文共享**\n   - Agent 之间需要通过文本传递信息\n   - 不像 newtype-profile 有完整的上下文共享机制\n\n4. **状态管理**\n   - 需要手动维护 Agent 之间的状态\n   - 建议配合 planning-with-files 使用\n\n---\n\n## 总结\n\nAI Agent Team SKILL 提供了一个简化版的 newtype-profile 架构：\n\n✅ **保留了核心价值**:\n- 多角色协作模式\n- 任务分类系统\n- 结构化工作流程\n\n✅ **适配 Claude Code**:\n- 使用 SKILL 机制\n- 遵循 SKILL.md 规范\n- 可与其他 SKILL 配合\n\n✅ **实用性强**:\n- 适用于复杂任务\n- 提升内容质量\n- 规范工作流程\n\n**灵感来源**: [newtype-01/newtype-profile](https://github.com/newtype-01/newtype-profile)\n**原项目**: 基于 oh-my-opencode 改造\n**作者**: 黄益贺 (huangyihe)\n\n---\n\n**版本**: 1.0.0\n**最后更新**: 2026-01-15\n**维护者**: SUNNYEUNG\n","readmeExcerpt":"--- name: ai-agent-team version: \"1.0.0\" description: \"AI Agent 协作团队系统 - 基于 newtype-profile 架构。模拟编辑团队模型，通过多个专业 Agent 协作完成复杂任务。适用于内容创作、研究分析、知识管理等场景。核心 Agent: chief(主编/协调者), researcher(研究员), writer(作者), editor(编辑), fact-checker(核查员), archivist(档案员)。支持任务分类、并行处理、质量验证等高级协作模式。触发词: 'agent team', '协作', '研究分析', '内容创作', '多角度分析'\" user-invocable: true --- AI Agent Team SKILL 概述 基于 $1 架构的 AI Agent 协作系统，将复杂任务分配给专业化的 Agent 团队协作完成。 ","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"[Chief] 请帮我规划这个内容创作项目的完整流程"},{"language":"text","snippet":"[@researcher] 研究一下 AI 在 2024 年的发展趋势"},{"language":"text","snippet":"[@writer] 基于研究结果，撰写一篇关于 AI 趋势的文章"},{"language":"text","snippet":"[@editor] 审查并优化这篇文章的结构和表达"},{"language":"text","snippet":"[@fact-checker] 验证文章中提到的数据和事实"},{"language":"text","snippet":"[@archivist] 查找我们之前关于类似主题的文档"}],"parameters":{},"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["typescript"],"docsSourceLabel":"GITHUB OPENCLEW","editorialOverview":"AI Agent 协作团队系统 - 基于 newtype-profile 架构。模拟编辑团队模型，通过多个专业 Agent 协作完成复杂任务。适用于内容创作、研究分析、知识管理等场景。核心 Agent: chief(主编/协调者), researcher(研究员), writer(作者), editor(编辑), fact-checker(核查员), archivist(档案员)。支持任务分类、并行处理、质量验证等高级协作模式。触发词: 'agent team', '协作', '研究分析', '内容创作', '多角度分析' --- name: ai-agent-team version: \"1.0.0\" description: \"AI Agent 协作团队系统 - 基于 newtype-profile 架构。模拟编辑团队模型，通过多个专业 Agent 协作完成复杂任务。适用于内容创作、研究分析、知识管理等场景。核心 Agent: chief(主编/协调者), researcher(研究员), writer(作者), editor(编辑), fact-checker(核查员), archivist(档案员)。支持任务分类、并行处理、质量验证等高级协作模式。触发词: 'agent team', '协作', '研究分析', '内容创作', '多角度分析'\" user-invocable: true --- AI Agent Team SKILL 概述 基于 $1 架构的 AI Agent 协作系统，将复杂任务分配给专业化的 Agent 团队协作完成。","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":361,"uniquenessScore":63,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-04-15T05:21:22.124Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-04-15T05:21:22.124Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-09T19:20:32.753Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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