{"id":"05ebb2ca-1a52-4812-bab2-bf404fbbbced","entityType":"agent","slug":"crewai-kevinten-ai-ai-agent-crewai","name":"ai-agent-crewai","canonicalUrl":"https://www.xpersona.co/agent/crewai-kevinten-ai-ai-agent-crewai","canonicalPath":"/agent/crewai-kevinten-ai-ai-agent-crewai","generatedAt":"2026-10-09T02:38:19.436Z","source":"GITHUB_OPENCLEW","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-05-18T06:45:23.693Z","emptyReason":null},"description":"CrewAI 多智能体编排学习与实践 — 核心概念速览、学习路线、实战案例（Meeting Agent 改造） <p align=\"center\"> <img src=\"assets/banner.png\" alt=\"AI Multi-Agent Orchestration\" width=\"600\" /> </p> <h1 align=\"center\">ai-agent-crewai</h1> <p align=\"center\"> 使用 <a href=\"https://crewai.com/\">CrewAI</a> 框架学习和实践多智能体编排（Multi-Agent Orchestration） </p> <p align=\"center\"> <img src=\"https://img.shields.io/badge/Python-3.10~3.13-blue?logo=python&logoColor=white\" /> <img src=\"https://img.shields.io/badge/CrewAI-Framework-","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. Last updated 5/18/2026.","installCommand":"git clone https://github.com/kevinten-ai/ai-agent-crewai.git","sourceUrl":"https://github.com/kevinten-ai/ai-agent-crewai","homepage":null,"primaryLinks":[{"label":"View Source","url":"https://github.com/kevinten-ai/ai-agent-crewai","kind":"source"}],"safetyScore":66,"overallRank":22,"popularityScore":0,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"CrewAI 多智能体编排学习与实践 — 核心概念速览、学习路线、实战案例（Meeting Agent 改造） <p align=\"center\"> <img src=\"assets/banner.png\" alt=\"AI Multi-Agent Orchestration\" width=\"600\" /> </p> <"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-05-18T06:45:23.693Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[{"label":"crewai","status":"self-declared"},{"label":"multi-agent","status":"self-declared"}],"verifiedCount":0,"selfDeclaredCount":3,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"},{"key":"crewai","type":"capability","support":"supported","confidenceSource":"profile","notes":"Declared in agent profile metadata"},{"key":"multi-agent","type":"capability","support":"supported","confidenceSource":"profile","notes":"Declared in agent profile metadata"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"}},"adoption":{"evidence":{"source":"no-adoption-signals","verified":false,"confidence":"low","updatedAt":"2026-05-18T06:45:23.693Z","emptyReason":"No source adoption metrics were available."},"stars":0,"forks":0,"downloads":null,"packageName":null,"latestVersion":null,"tractionLabel":null},"release":{"evidence":{"source":"agent-index","verified":false,"confidence":"medium","updatedAt":"2026-05-18T06:45:23.693Z","emptyReason":null},"lastUpdatedAt":"2026-05-18T06:45:23.693Z","lastCrawledAt":"2026-05-18T06:45:23.693Z","lastIndexedAt":null,"nextCrawlAt":"2026-05-25T06:45:23.693Z","lastVerifiedAt":null,"highlights":[]},"execution":{"evidence":{"source":"GITHUB OPENCLEW","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"git clone https://github.com/kevinten-ai/ai-agent-crewai.git","setupComplexity":"low","setupSteps":["Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"GITHUB_OPENCLEW","generatedAt":"2026-10-09T02:38:19.436Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-kevinten-ai-ai-agent-crewai/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"GITHUB OPENCLEW","verified":false,"confidence":"high","updatedAt":"2026-05-18T06:45:23.693Z","emptyReason":null},"readme":"<p align=\"center\">\n  <img src=\"assets/banner.png\" alt=\"AI Multi-Agent Orchestration\" width=\"600\" />\n</p>\n\n<h1 align=\"center\">ai-agent-crewai</h1>\n\n<p align=\"center\">\n  使用 <a href=\"https://crewai.com/\">CrewAI</a> 框架学习和实践多智能体编排（Multi-Agent Orchestration）\n</p>\n\n<p align=\"center\">\n  <img src=\"https://img.shields.io/badge/Python-3.10~3.13-blue?logo=python&logoColor=white\" />\n  <img src=\"https://img.shields.io/badge/CrewAI-Framework-purple?logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCI+PHRleHQgeT0iMTgiIGZvbnQtc2l6ZT0iMTYiPvCfpJY8L3RleHQ+PC9zdmc+\" />\n  <img src=\"https://img.shields.io/badge/Package_Manager-uv-green?logo=astral&logoColor=white\" />\n</p>\n\n---\n\n## 环境要求\n\n- **Python** >=3.10, <3.14\n- **[uv](https://github.com/astral-sh/uv)** — CrewAI 推荐的包管理器（比 pip 快 10-100x）\n\n## 快速安装\n\n```bash\n# 1. 安装 uv（macOS/Linux）\ncurl -LsSf https://astral.sh/uv/install.sh | sh\n\n# 2. 安装 CrewAI CLI\nuv tool install crewai\n\n# 验证安装\nuv tool list\n```\n\n## 创建第一个 Crew 项目\n\n```bash\n# 脚手架生成项目\ncrewai create crew my_first_crew\ncd my_first_crew\n\n# 安装依赖\ncrewai install\n\n# 运行\ncrewai run\n```\n\n<details>\n<summary>📂 生成的项目结构</summary>\n\n```\nmy_first_crew/\n├── src/my_first_crew/\n│   ├── config/\n│   │   ├── agents.yaml      # 智能体定义（角色、目标、背景）\n│   │   └── tasks.yaml        # 任务定义（描述、期望输出）\n│   ├── crew.py               # Crew 编排逻辑\n│   ├── main.py               # 入口文件\n│   └── tools/                # 自定义工具\n├── pyproject.toml\n└── .env                      # API Keys\n```\n\n</details>\n\n---\n\n## 核心概念速览\n\n<p align=\"center\">\n  <img src=\"assets/concepts.png\" alt=\"Core Concepts: Agent → Task → Crew → Flow\" width=\"560\" />\n</p>\n\n### 1. Agent（智能体）\n\n自主实体，具有角色、目标和背景故事。\n\n```yaml\n# agents.yaml\nresearcher:\n  role: \"{topic} Senior Data Researcher\"\n  goal: \"Uncover cutting-edge developments in {topic}\"\n  backstory: \"You're a seasoned researcher with a knack for uncovering the latest developments...\"\n```\n\n> 关键参数：`role` `goal` `backstory` `llm` `tools` `memory` `verbose` `allow_delegation` `max_iter` `reasoning`\n\n### 2. Task（任务）\n\n分配给智能体的具体工作单元。\n\n```yaml\n# tasks.yaml\nresearch_task:\n  description: \"Conduct thorough research about {topic}...\"\n  expected_output: \"A list with 10 bullet points of relevant information\"\n  agent: researcher\n  output_file: report.md\n```\n\n### 3. Crew（团队）\n\n将智能体和任务组合在一起协作。\n\n```python\nfrom crewai import Agent, Crew, Process, Task\nfrom crewai.project import CrewBase, agent, crew, task\n\n@CrewBase\nclass MyCrew():\n    @agent\n    def researcher(self) -> Agent:\n        return Agent(config=self.agents_config['researcher'], tools=[SerperDevTool()])\n\n    @task\n    def research_task(self) -> Task:\n        return Task(config=self.tasks_config['research_task'])\n\n    @crew\n    def crew(self) -> Crew:\n        return Crew(agents=self.agents, tasks=self.tasks, process=Process.sequential, verbose=True)\n```\n\n### 4. Flow（工作流）\n\n事件驱动的编排层，用于连接多个 Crew、管理状态和控制执行流程。\n\n```python\nfrom crewai.flow.flow import Flow, listen, start\n\nclass MyFlow(Flow):\n    @start()\n    def initialize(self):\n        return \"start data\"\n\n    @listen(initialize)\n    def process(self, data):\n        # 可以在这里调用 Crew\n        result = MyCrew().crew().kickoff(inputs={\"topic\": data})\n        return result.raw\n```\n\n> 核心装饰器：`@start()` 入口方法 · `@listen(method)` 监听触发 · `@router(method)` 条件路由 · `and_()` / `or_()` 组合条件\n\n### 5. Tools（工具）\n\n智能体可以使用的外部能力（搜索、API 调用、文件操作等）。\n\n```bash\nuv add crewai-tools\n```\n\n---\n\n## 学习路线\n\n<p align=\"center\">\n  <img src=\"assets/roadmap.png\" alt=\"Learning Roadmap\" width=\"400\" />\n</p>\n\n| 阶段 | 内容 | 资源 |\n|:---:|------|------|\n| **1. 入门** | 安装 + 跑通第一个 Crew | [Quickstart](https://docs.crewai.com/en/quickstart) |\n| **2. 基础** | 理解 Agent / Task / Crew 参数 | [Agents](https://docs.crewai.com/en/concepts/agents) · [Tasks](https://docs.crewai.com/en/concepts/tasks) · [Crews](https://docs.crewai.com/en/concepts/crews) |\n| **3. 工具** | 学习内置工具 + 自定义工具 | [Tools](https://docs.crewai.com/en/concepts/tools) |\n| **4. 进阶** | Flow 编排多 Crew 工作流 | [Flows](https://docs.crewai.com/en/concepts/flows) |\n| **5. 实战** | 跑通官方示例项目 | [crewAI-examples](https://github.com/crewAIInc/crewAI-examples) |\n| **6. 深入** | Memory / Knowledge / RAG | [Memory](https://docs.crewai.com/en/concepts/memory) · [Knowledge](https://docs.crewai.com/en/concepts/knowledge) |\n\n---\n\n## 实战案例：用 CrewAI 改造 Meeting Agent\n\n> 基于 [ava-agent/meeting-agent](https://github.com/ava-agent/meeting-agent) — 一站式 AI 会议策划平台\n\n### 现状问题\n\nmeeting-agent 有 4 个 AI 角色（议程、演讲稿、海报、伴手礼），但它们**完全独立运行、互不感知**：\n\n```\n现状：4 个独立 LLM 调用 → Promise.all() 并行 → 各自输出，风格不统一\n```\n\n### CrewAI 改造方案\n\n<p align=\"center\">\n  <img src=\"assets/case-meeting.png\" alt=\"Meeting Agent CrewAI Architecture\" width=\"560\" />\n</p>\n\n用 CrewAI 将 4 个独立角色重构为**协作式 Crew**，Agent 之间共享上下文、链式传递输出：\n\n```yaml\n# agents.yaml\nagenda_planner:\n  role: \"会议策划专家\"\n  goal: \"根据会议信息生成结构化议程，包含时间块、议题和负责人\"\n  backstory: \"你是一位拥有10年大型会议策划经验的专家...\"\n\nspeech_writer:\n  role: \"演讲稿撰写专家\"\n  goal: \"根据议程内容撰写开场白和主题演讲稿\"\n  backstory: \"你是一位资深演讲稿撰写者，擅长根据议程上下文创作...\"\n\nposter_designer:\n  role: \"平面设计师\"\n  goal: \"根据议程和演讲主题输出海报设计方案（配色、布局、文案）\"\n  backstory: \"你是一位创意设计师，能从会议内容中提炼视觉主题...\"\n\ngift_consultant:\n  role: \"活动策划顾问\"\n  goal: \"根据会议类型、预算和参会人群推荐伴手礼方案\"\n  backstory: \"你是一位活动策划顾问，熟悉各类商务礼品...\"\n\nqa_reviewer:\n  role: \"质量审核专家\"\n  goal: \"审核所有输出的一致性、专业性和完整性\"\n  backstory: \"你是一位严谨的质量审核员...\"\n```\n\n```yaml\n# tasks.yaml — 链式依赖，上游输出自动注入下游\nagenda_task:\n  description: \"为 {meeting_type} 生成详细议程：{title}，{duration}，{attendees}人参会\"\n  expected_output: \"结构化议程表，含时间、议题、负责人、形式\"\n  agent: agenda_planner\n\nspeech_task:\n  description: \"根据以上议程，撰写开场致辞和主旨演讲稿\"\n  expected_output: \"完整演讲稿，markdown 格式，含时长标注\"\n  agent: speech_writer\n  context: [agenda_task]          # 引用议程输出\n\nposter_task:\n  description: \"根据议程和演讲主题，输出海报设计方案\"\n  expected_output: \"设计brief：主题、配色方案、布局描述、核心文案\"\n  agent: poster_designer\n  context: [agenda_task, speech_task]  # 引用议程+演讲\n\ngift_task:\n  description: \"根据会议类型和预算 {budget}，推荐伴手礼方案\"\n  expected_output: \"3套方案：经济/标准/精品，含品名、单价、总预算\"\n  agent: gift_consultant\n\nreview_task:\n  description: \"审核以上所有输出，检查一致性和完整性\"\n  expected_output: \"审核报告：通过/需修改，附具体修改建议\"\n  agent: qa_reviewer\n  context: [agenda_task, speech_task, poster_task, gift_task]\n```\n\n### 改造前 vs 改造后\n\n| 维度 | 改造前 | CrewAI 改造后 |\n|------|--------|-------------|\n| Agent 间依赖 | 零，各自独立 | 链式：议程→演讲→海报→伴手礼→审核 |\n| 输出一致性 | 风格可能不一致 | 共享 context，风格统一 |\n| 质量保障 | 无 | QA Agent 审核，不合格则重新生成 |\n| 流程适配 | 固定流程 | Flow 按会议类型（年会/技术分享/发布会）走不同路径 |\n| 可扩展性 | 加角色需改代码 | YAML 加配置即可 |\n\n### 用 Flow 编排不同会议类型\n\n```python\nfrom crewai.flow.flow import Flow, start, listen, router\n\nclass MeetingFlow(Flow):\n    @start()\n    def classify_meeting(self):\n        \"\"\"识别会议类型\"\"\"\n        return classify(self.state.meeting_data)\n\n    @router(classify_meeting)\n    def route_by_type(self, meeting_type):\n        if meeting_type == \"annual_gala\":\n            return \"full_planning\"        # 年会：全套 5 Agent\n        elif meeting_type == \"tech_talk\":\n            return \"light_planning\"       # 技术分享：议程+演讲 2 Agent\n        return \"standard_planning\"\n\n    @listen(\"full_planning\")\n    def run_full_crew(self):\n        return FullMeetingCrew().crew().kickoff(inputs=self.state.meeting_data)\n\n    @listen(\"light_planning\")\n    def run_light_crew(self):\n        return LightMeetingCrew().crew().kickoff(inputs=self.state.meeting_data)\n```\n\n---\n\n## 常用 CLI 命令\n\n| 命令 | 说明 |\n|------|------|\n| `crewai create crew <name>` | 创建新 Crew 项目 |\n| `crewai create flow <name>` | 创建新 Flow 项目 |\n| `crewai install` | 安装项目依赖 |\n| `crewai run` | 运行项目 |\n| `crewai test` | 测试 Crew |\n| `crewai log-tasks-outputs` | 查看任务输出日志 |\n\n---\n\n## 学习资源\n\n**官方资源**\n\n| 资源 | 链接 |\n|------|------|\n| 官方文档 | [docs.crewai.com](https://docs.crewai.com/en/introduction) |\n| GitHub 仓库 | [crewAIInc/crewAI](https://github.com/crewAIInc/crewAI) |\n| 完整示例项目 | [crewAI-examples](https://github.com/crewAIInc/crewAI-examples) |\n| 快速上手 Demo | [crewAI-quickstarts](https://github.com/crewAIInc/crewAI-quickstarts) |\n| 官方博客 | [blog.crewai.com](https://blog.crewai.com/) |\n| 社区论坛 | [community.crewai.com](https://community.crewai.com/) |\n\n**教程与文章**\n\n- [Build your First CrewAI Agents（官方博客）](https://blog.crewai.com/getting-started-with-crewai-build-your-first-crew/)\n- [CrewAI: A Guide With Examples — DataCamp](https://www.datacamp.com/tutorial/crew-ai)\n- [What is crewAI? — IBM](https://www.ibm.com/think/topics/crew-ai)\n- [CrewAI — AWS Prescriptive Guidance](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-frameworks/crewai.html)\n\n**Quickstart 专题**\n\n| 示例 | 内容 |\n|------|------|\n| Collaboration | 多智能体协作模式 |\n| Custom LLM | 接入自定义 LLM（Anthropic、本地模型等）|\n| Guardrails | 安全护栏与输出验证 |\n| Planning | 任务规划与编排 |\n| Reasoning | 高级推理模式 |\n","readmeExcerpt":"<p align=\"center\"> <img src=\"assets/banner.png\" alt=\"AI Multi-Agent Orchestration\" width=\"600\" /> </p> <h1 align=\"center\">ai-agent-crewai</h1> <p align=\"center\"> 使用 <a href=\"https://crewai.com/\">CrewAI</a> 框架学习和实践多智能体编排（Multi-Agent Orchestration） </p> <p align=\"center\"> <img src=\"https://img.shields.io/badge/Python-3.10~3.13-blue?logo=python&logoColor=white\" /> <img src=\"https://img.shields.io/badge/CrewAI-Framework-","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"curl -LsSf https://astral.sh/uv/install.sh | sh"},{"language":"bash","snippet":"# 1. 安装 uv（macOS/Linux）\ncurl -LsSf https://astral.sh/uv/install.sh | sh\n\n# 2. 安装 CrewAI CLI\nuv tool install crewai\n\n# 验证安装\nuv tool list"},{"language":"bash","snippet":"# 脚手架生成项目\ncrewai create crew my_first_crew\ncd my_first_crew\n\n# 安装依赖\ncrewai install\n\n# 运行\ncrewai run"},{"language":"text","snippet":"my_first_crew/\n├── src/my_first_crew/\n│   ├── config/\n│   │   ├── agents.yaml      # 智能体定义（角色、目标、背景）\n│   │   └── tasks.yaml        # 任务定义（描述、期望输出）\n│   ├── crew.py               # Crew 编排逻辑\n│   ├── main.py               # 入口文件\n│   └── tools/                # 自定义工具\n├── pyproject.toml\n└── .env                      # API Keys"},{"language":"yaml","snippet":"# agents.yaml\nresearcher:\n  role: \"{topic} Senior Data Researcher\"\n  goal: \"Uncover cutting-edge developments in {topic}\"\n  backstory: \"You're a seasoned researcher with a knack for uncovering the latest developments...\""},{"language":"yaml","snippet":"# tasks.yaml\nresearch_task:\n  description: \"Conduct thorough research about {topic}...\"\n  expected_output: \"A list with 10 bullet points of relevant information\"\n  agent: researcher\n  output_file: report.md"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["python"],"docsSourceLabel":"GITHUB OPENCLEW","editorialOverview":"CrewAI 多智能体编排学习与实践 — 核心概念速览、学习路线、实战案例（Meeting Agent 改造） <p align=\"center\"> <img src=\"assets/banner.png\" alt=\"AI Multi-Agent Orchestration\" width=\"600\" /> </p> <h1 align=\"center\">ai-agent-crewai</h1> <p align=\"center\"> 使用 <a href=\"https://crewai.com/\">CrewAI</a> 框架学习和实践多智能体编排（Multi-Agent Orchestration） </p> <p align=\"center\"> <img src=\"https://img.shields.io/badge/Python-3.10~3.13-blue?logo=python&logoColor=white\" /> <img src=\"https://img.shields.io/badge/CrewAI-Framework-","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":374,"uniquenessScore":64,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-05-18T06:45:23.693Z","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":"2026-05-18T06:45:23.693Z","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":"2026-10-09T02:38:19.436Z","emptyReason":null},"items":[{"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. Unified access to frontier LLMs","url":"https://github.com/CherryHQ/cherry-studio","homepage":"https://cherry-ai.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-11T14:38:40.986Z","createdAt":"2026-02-25T03:38:19.379Z","downloads":null},{"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":"2026-04-10T18:48:31.762Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"6f6582d0-5d76-4f0f-b81d-86520247950b","entityType":"agent","canonicalPath":"/agent/copilotkit-copilotkit","slug":"copilotkit-copilotkit","name":"CopilotKit","description":"The Frontend for Agents & Generative UI. React + Angular","url":"https://github.com/CopilotKit/CopilotKit","homepage":"https://docs.copilotkit.ai","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-03-25T09:50:57.846Z","createdAt":"2026-02-25T03:39:14.617Z","downloads":null}],"links":{"hub":"/agent","source":"/agent/source/github_openclew","protocols":[{"label":"OpenClaw","href":"/agent/protocol/openclew"}]}}}