{
  "schema_version": 1,
  "report_date": "2026-06-28",
  "title": "AI 日报 2026-06-28",
  "summary": "今天最值得看的主线有 OpenAI披露安全治理和平台控制变化；Anthropic披露模型评估和研究结果；Alibaba Cloud披露 agent 与开发者工具能力；热门博客这轮主要看 agent 和开发工具的落地边界。",
  "hero_highlights": [
    {
      "title": "Google Keyword更新AI 产品、平台或工程实践",
      "url": "https://blog.google/products-and-platforms/products/gemini/gemini-help-avoid-jetlag/",
      "reason": "信号集中在 AI 产品、模型或平台策略的实际变化",
      "what_happened": "Google Keyword更新AI 产品、平台或工程实践，材料覆盖功能变化、使用场景、接入方式、限制条件和后续部署边界，边界落在公开材料仍需要回到原文核对入口、权限、价格和适用范围",
      "why_watch": "信号集中在 AI 产品、模型或平台策略的实际变化",
      "category": "model_platform",
      "source_item_ref": "https://blog.google/products-and-platforms/products/gemini/gemini-help-avoid-jetlag/"
    },
    {
      "title": "OpenAI披露安全治理和平台控制变化",
      "url": "https://openai.com/index/previewing-gpt-5-6-sol",
      "reason": "工程侧价值集中在 agent、开发工具和自动化工作流接入",
      "what_happened": "OpenAI更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性",
      "why_watch": "工程侧价值集中在 agent、开发工具和自动化工作流接入",
      "category": "product_tool",
      "source_item_ref": "https://openai.com/index/previewing-gpt-5-6-sol"
    },
    {
      "title": "Anthropic披露模型评估和研究结果",
      "url": "https://www.anthropic.com/research/economic-index-june-2026-report",
      "reason": "工程价值集中在代码、权重、示例和生态复用条件",
      "what_happened": "Anthropic更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性",
      "why_watch": "工程价值集中在代码、权重、示例和生态复用条件",
      "category": "china_open_source_community",
      "source_item_ref": "https://www.anthropic.com/research/economic-index-june-2026-report"
    }
  ],
  "stories": [
    {
      "story_id": "story-content-openai-news-previewing-gpt-5-6-sol-a-next-generation-model",
      "title": "OpenAI说明安全治理和平台控制变化",
      "importance": "general",
      "trend": "AI industry",
      "event_date": "2026-06-26",
      "primary_entity": "OpenAI News RSS",
      "event_type": "signal",
      "object": "OpenAI披露安全治理和平台控制变化",
      "what_happened": "OpenAI 在官方页面预览 GPT-5.6 Sol，称其是下一代模型，重点提升编码、科学和网络安全能力，并配套其目前最先进的安全栈。",
      "why_it_matters": "如果这些能力进入产品和 API，企业评估模型时需要同时看能力增量和安全控制，而不是只看单项 benchmark。",
      "evidence_level": "multi_source",
      "sources": [
        {
          "label": "OpenAI News RSS",
          "url": "https://openai.com/index/previewing-gpt-5-6-sol",
          "type": "official"
        },
        {
          "label": "OpenAI Blog RSS",
          "url": "https://openai.com/index/previewing-gpt-5-6-sol",
          "type": "official"
        },
        {
          "label": "OpenAI Company News RSS",
          "url": "https://openai.com/index/previewing-gpt-5-6-sol",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-anthropic-research-jun-26-2026-economic-research-anthropic-economic-inde",
      "title": "Anthropic公布模型评估和研究结果",
      "importance": "general",
      "trend": "open source AI",
      "event_date": "2026-06-26",
      "primary_entity": "Anthropic Research",
      "event_type": "research",
      "object": "Anthropic披露模型评估和研究结果",
      "what_happened": "Anthropic 发布 2026 年 6 月 Economic Index 报告 Cadences，并把它放在经济研究系列中，和 Frontier Red Team Project、agentic coding 等近期研究并列。",
      "why_it_matters": "这类使用与经济研究信号能帮助产品和策略负责人判断 AI 在工作流中的采用节奏，尤其是哪些任务正在从试验走向持续使用。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Anthropic Research",
          "url": "https://www.anthropic.com/research/economic-index-june-2026-report",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-alibaba-cloud-blog-apsaradb-rds-debuts-rdshermes-empowering-database-ai",
      "title": "ApsaraDB RDS推出RDSHermes数据库AI agent服务",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-26",
      "primary_entity": "Alibaba Cloud Blog",
      "event_type": "signal",
      "object": "Alibaba Cloud披露 agent 与开发者工具能力",
      "what_happened": "阿里云介绍 ApsaraDB for RDS 上的 RDSHermes，定位为安全、可自我演进的数据库原生 AI agent 服务，用于让数据库场景中的 agent 能够自主迭代。",
      "why_it_matters": "数据库 agent 涉及权限、数据访问和自动操作边界，RDSHermes 把评估重点从单次问答转向生产数据库里的安全执行和持续优化。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Alibaba Cloud Blog",
          "url": "https://www.alibabacloud.com/blog/apsaradb-rds-debuts-rdshermes-empowering-database-ai-agents-to-evolve-autonomously_603310",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-alibaba-cloud-blog-alibaba-cloud-idaas-earns-first-eal3-certification-in",
      "title": "Alibaba Cloud说明安全治理和平台控制变化",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-26",
      "primary_entity": "Alibaba Cloud Blog",
      "event_type": "signal",
      "object": "Alibaba Cloud披露安全治理和平台控制变化",
      "what_happened": "阿里云称其 IDaaS 在中国大陆身份安全领域获得 EAL3+ 认证，并把该认证作为身份安全能力的合规背书。",
      "why_it_matters": "对需要统一身份、访问控制和审计的企业来说，认证结果会进入供应商准入、安全评估和合规材料。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Alibaba Cloud Blog",
          "url": "https://www.alibabacloud.com/blog/alibaba-cloud-idaas-earns-first-eal3%2B-certification-in-identity-security-in-mainland-china_603308",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-alibaba-cloud-blog-alibaba-cloud-named-a-leader-in-omdia-market-radar-ag",
      "title": "阿里云在Omdia亚太Agentic AI云厂商评估中列为Leader",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-26",
      "primary_entity": "Alibaba Cloud Blog",
      "event_type": "signal",
      "object": "Alibaba Cloud披露 agent 与开发者工具能力",
      "what_happened": "阿里云称自己在 Omdia《Agentic AI Cloud Titans in Asia & Oceania, 2026》Market Radar 中被列为 Leader，并在九个维度中的六项获得最高排名，重点强调全栈 agentic AI 范式。",
      "why_it_matters": "这给云厂商 agentic AI 能力提供了第三方评估线索，采购和平台团队可据此对比产品栈完整度、区域覆盖和行业落地案例。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Alibaba Cloud Blog",
          "url": "https://www.alibabacloud.com/blog/alibaba-cloud-named-a-leader-in-omdia-market-radar-agentic-ai-cloud-titans-in-asia-%26-oceania-2026_603309",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-google-keyword-here-s-how-gemini-can-help-you-avoid-jetlag",
      "title": "Google Keyword Blog: Gemini Help Avoid Jetlag",
      "importance": "general",
      "trend": "AI industry",
      "event_date": "2026-06-26",
      "primary_entity": "Google Keyword Blog",
      "event_type": "signal",
      "object": "Google Keyword更新AI 产品、平台或工程实践",
      "what_happened": "Google 在 Keyword Blog 介绍 Gemini app 的旅行用法：用户授权后，可以让 Gemini 根据远行计划给出减少时差影响的建议，帮助安排睡眠和行程节奏。",
      "why_it_matters": "这是 Gemini 从通用聊天进入个人旅行助手场景的一个具体例子，产品负责人可观察权限授权、日程上下文和个性化建议如何组合。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Google Keyword Blog",
          "url": "https://blog.google/products-and-platforms/products/gemini/gemini-help-avoid-jetlag/",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-mit-technology-review-the-download-brain-melting-heatwaves-and-unprecede",
      "title": "MIT Technology Review: The Download Heatwaves Brain Health Openai Restrictions",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-26",
      "primary_entity": "MIT Technology Review",
      "event_type": "signal",
      "object": "OpenAI更新agent 工作流和开发工具能力",
      "what_happened": "MIT Technology Review 的 The Download 当日简报同时提到热浪对大脑健康的影响研究，以及关于 OpenAI 限制的报道线索；该条的可核验事实来自媒体简报，正式引用前应回到原始研究或官方说明。",
      "why_it_matters": "它提醒编辑区分媒体摘要和一手发布，避免把简报中的多个议题合并成未经核验的 OpenAI 主体结论。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "MIT Technology Review",
          "url": "https://www.technologyreview.com/2026/06/26/1139780/the-download-heatwaves-brain-health-openai-restrictions/",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-github-changelog-mai-code-1-flash-for-copilot-business-and-copilot-enter",
      "title": "GitHub Changelog发布 Copilot 与企业可用范围变化",
      "importance": "general",
      "trend": "open source AI",
      "event_date": "2026-06-26",
      "primary_entity": "GitHub Changelog",
      "event_type": "launch",
      "object": "GitHub Changelog披露 Copilot 与企业可用范围变化",
      "what_happened": "GitHub Changelog 宣布 Microsoft AI 的 MAI-Code-1-Flash 已面向 Copilot Business 和 Copilot Enterprise 正式可用，延续该模型此前在 Copilot 多个入口的扩展。",
      "why_it_matters": "企业 Copilot 管理员和开发平台负责人需要确认该模型的可用范围、策略配置和默认启用方式，再决定是否纳入团队编码辅助选项。",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "GitHub Changelog",
          "url": "https://github.blog/changelog/2026-06-26-mai-code-1-flash-for-copilot-business-and-copilot-enterprise",
          "type": "github"
        }
      ]
    }
  ],
  "main_items": [
    {
      "title": "OpenAI说明安全治理和平台控制变化",
      "editorial_category": "ai_industry",
      "event_date": "2026-06-26",
      "url": "https://openai.com/index/previewing-gpt-5-6-sol",
      "source": "OpenAI News RSS",
      "tier": "T0",
      "entities": [
        "OpenAI News RSS"
      ],
      "summary": "OpenAI更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**OpenAI披露安全治理和平台控制变化**：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "当前公开的是部署方式、权限、上下文管理和失败恢复边界。",
        "这会影响研发团队安排 agent 工具接入顺序、权限设计、评估回放和落地成本。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Anthropic公布模型评估和研究结果",
      "editorial_category": "open_source",
      "event_date": "2026-06-26",
      "url": "https://www.anthropic.com/research/economic-index-june-2026-report",
      "source": "Anthropic Research",
      "tier": "T0",
      "entities": [
        "Anthropic Research"
      ],
      "summary": "Anthropic更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**Anthropic披露模型评估和研究结果**：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "当前公开的是代码接口、许可证、维护节奏、集成门槛和团队可复用边界。",
        "这会影响研发团队是否把它放进 PoC、评估清单、现有工作流或长期维护计划。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "ApsaraDB RDS推出RDSHermes数据库AI agent服务",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-26",
      "url": "https://www.alibabacloud.com/blog/apsaradb-rds-debuts-rdshermes-empowering-database-ai-agents-to-evolve-autonomously_603310",
      "source": "Alibaba Cloud Blog",
      "tier": "T0",
      "entities": [
        "Alibaba Cloud Blog"
      ],
      "summary": "Alibaba Cloud更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**Alibaba Cloud披露 agent 与开发者工**：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "当前公开的是部署方式、权限、上下文管理和失败恢复边界。",
        "这会影响研发团队安排 agent 工具接入顺序、权限设计、评估回放和落地成本。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Alibaba Cloud说明安全治理和平台控制变化",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-26",
      "url": "https://www.alibabacloud.com/blog/alibaba-cloud-idaas-earns-first-eal3%2B-certification-in-identity-security-in-mainland-china_603308",
      "source": "Alibaba Cloud Blog",
      "tier": "T0",
      "entities": [
        "Alibaba Cloud Blog"
      ],
      "summary": "Alibaba Cloud更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**Alibaba Cloud披露安全治理和平台控制变化**：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "当前公开的是生效范围、执行主体、例外条款、落地安排和责任边界。",
        "这类更新会直接牵动产品上线流程、风控口径、合规检查和责任分工。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "阿里云在Omdia亚太Agentic AI云厂商评估中列为Leader",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-26",
      "url": "https://www.alibabacloud.com/blog/alibaba-cloud-named-a-leader-in-omdia-market-radar-agentic-ai-cloud-titans-in-asia-%26-oceania-2026_603309",
      "source": "Alibaba Cloud Blog",
      "tier": "T0",
      "entities": [
        "Alibaba Cloud Blog"
      ],
      "summary": "Alibaba Cloud更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**Alibaba Cloud披露 agent 与开发者工**：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "当前公开的是部署方式、权限、上下文管理和失败恢复边界。",
        "这会影响研发团队安排 agent 工具接入顺序、权限设计、评估回放和落地成本。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Google Keyword Blog: Gemini Help Avoid Jetlag",
      "editorial_category": "ai_industry",
      "event_date": "2026-06-26",
      "url": "https://blog.google/products-and-platforms/products/gemini/gemini-help-avoid-jetlag/",
      "source": "Google Keyword Blog",
      "tier": "T0",
      "entities": [
        "Google Keyword Blog"
      ],
      "summary": "Google Keyword更新AI 产品、平台或工程实践，材料覆盖功能变化、使用场景、接入方式、限制条件和后续部署边界，边界落在公开材料仍需要回到原文核对入口、权限、价格和适用范围。",
      "bullets": [
        "**Google Keyword更新AI 产品、平台或工程**：材料把AI 产品、平台或工程实践落到功能变化、使用场景、接入方式、限制条件和后续部署边界，已披露事实集中在功能变化、适用场景、接入方式和限制条件。",
        "已披露细节覆盖适用对象、证据来源、执行安排、后续时间表和风险边界。",
        "这会影响产品团队判断路线优先级、接入时机、资源投入和后续风险预案。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "MIT Technology Review: The Download Heatwaves Brain Health Openai Restrictions",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-26",
      "url": "https://www.technologyreview.com/2026/06/26/1139780/the-download-heatwaves-brain-health-openai-restrictions/",
      "source": "MIT Technology Review",
      "tier": "T0",
      "entities": [
        "MIT Technology Review"
      ],
      "summary": "OpenAI更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**OpenAI更新agent 工作流和开发工具能力**：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "已披露细节覆盖适用对象、证据来源、执行安排、后续时间表和风险边界。",
        "这会影响产品团队判断路线优先级、接入时机、资源投入和后续风险预案。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "GitHub Changelog发布 Copilot 与企业可用范围变化",
      "editorial_category": "open_source",
      "event_date": "2026-06-26",
      "url": "https://github.blog/changelog/2026-06-26-mai-code-1-flash-for-copilot-business-and-copilot-enterprise",
      "source": "GitHub Changelog",
      "tier": "T2",
      "entities": [
        "GitHub Changelog"
      ],
      "summary": "该开源项目更新agent 工作流和开发工具能力，材料覆盖任务编排、上下文、权限控制、工程集成和失败恢复，边界落在落地质量取决于权限模型、评估回放、团队流程和可观测性。",
      "bullets": [
        "**GitHub Changelog披露 Copilot **：材料把agent 工作流和开发工具能力落到任务编排、上下文、权限控制、工程集成和失败恢复，已披露事实集中在agent 工作流、开发工具入口、权限控制和工程集成。",
        "当前公开的是代码接口、许可证、维护节奏、集成门槛和团队可复用边界。",
        "这会影响研发团队是否把它放进 PoC、评估清单、现有工作流或长期维护计划。"
      ],
      "importance": "general",
      "image_urls": []
    }
  ],
  "github_trending": [
    {
      "name": "calesthio/OpenMontage",
      "repo": "calesthio/OpenMontage",
      "readme_cache": {
        "key": "github-readme/calesthio/openmontage/main/unknown",
        "hit": true,
        "repo": "calesthio/openmontage",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/calesthio/OpenMontage/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/calesthio/OpenMontage",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 1,
      "source_rank": 1,
      "source_scope": "weekly:all",
      "previous_rank": 1,
      "rank_delta": 0,
      "trend": "same",
      "importance": "general",
      "description": "OpenMontage 是代理式自动化、工具调用和开发者工作流相关的开源项目，公开说明提到Agent 构建、工具调用和工作流编排等能力，并提供部署说明；评估时核对安装步骤、许可证、示例质量、近期维护和接入边界。 它把相关能力沉淀为代码、示例和集成入口，方便和同类方案做功能与工程成本比较。"
    },
    {
      "name": "DeusData/codebase-memory-mcp",
      "repo": "DeusData/codebase-memory-mcp",
      "readme_cache": {
        "key": "github-readme/deusdata/codebase-memory-mcp/main/unknown",
        "hit": true,
        "repo": "deusdata/codebase-memory-mcp",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/DeusData/codebase-memory-mcp",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 2,
      "source_rank": 2,
      "source_scope": "weekly:all",
      "previous_rank": 2,
      "rank_delta": 0,
      "trend": "same",
      "importance": "general",
      "description": "DeusData/codebase-memory-mcp 本周出现在开源榜单 weekly #2，本周 +7,592 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "kunchenguid/no-mistakes",
      "repo": "kunchenguid/no-mistakes",
      "readme_cache": {
        "key": "github-readme/kunchenguid/no-mistakes/main/unknown",
        "hit": true,
        "repo": "kunchenguid/no-mistakes",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/kunchenguid/no-mistakes/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/kunchenguid/no-mistakes",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 3,
      "source_rank": 3,
      "source_scope": "weekly:all",
      "previous_rank": 19,
      "rank_delta": 16,
      "trend": "up",
      "importance": "notable",
      "description": "kunchenguid/no-mistakes 本周出现在开源榜单 weekly #3，本周 +1,744 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "google-labs-code/design.md",
      "repo": "google-labs-code/design.md",
      "readme_cache": {
        "key": "github-readme/google-labs-code/design.md/main/unknown",
        "hit": true,
        "repo": "google-labs-code/design.md",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/google-labs-code/design.md/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/google-labs-code/design.md",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 4,
      "source_rank": 4,
      "source_scope": "weekly:all",
      "previous_rank": 12,
      "rank_delta": 8,
      "trend": "up",
      "importance": "general",
      "description": "google-labs-code/design.md 本周出现在开源榜单 weekly #4，本周 +4,618 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "ZhuLinsen/daily_stock_analysis",
      "repo": "ZhuLinsen/daily_stock_analysis",
      "readme_cache": {
        "key": "github-readme/zhulinsen/daily_stock_analysis/main/unknown",
        "hit": true,
        "repo": "zhulinsen/daily_stock_analysis",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/ZhuLinsen/daily_stock_analysis/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/ZhuLinsen/daily_stock_analysis",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 5,
      "source_rank": 5,
      "source_scope": "weekly:all",
      "previous_rank": 9,
      "rank_delta": 4,
      "trend": "up",
      "importance": "general",
      "description": "daily_stock_analysis 是代理式自动化、工具调用和开发者工作流相关的开源项目，公开说明提到Agent 构建、记忆或知识检索、API/SDK 适配等能力，并提供部署说明；评估时核对安装步骤、许可证、示例质量、近期维护和接入边界。 它把相关能力沉淀为代码、示例和集成入口，方便和同类方案做功能与工程成本比较。"
    },
    {
      "name": "penpot/penpot",
      "repo": "penpot/penpot",
      "readme_cache": {
        "key": "github-readme/penpot/penpot/main/unknown",
        "hit": true,
        "repo": "penpot/penpot",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/penpot/penpot/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/penpot/penpot",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 6,
      "source_rank": 6,
      "source_scope": "weekly:all",
      "previous_rank": 5,
      "rank_delta": -1,
      "trend": "down",
      "importance": "general",
      "description": "penpot 是代理式自动化、工具调用和开发者工作流相关的开源项目，公开说明提到工具调用和工作流编排等能力，并提供部署说明；评估时核对安装步骤、许可证、示例质量、近期维护和接入边界。 它把相关能力沉淀为代码、示例和集成入口，方便和同类方案做功能与工程成本比较。"
    },
    {
      "name": "Panniantong/Agent-Reach",
      "repo": "Panniantong/Agent-Reach",
      "readme_cache": {
        "key": "github-readme/panniantong/agent-reach/main/unknown",
        "hit": true,
        "repo": "panniantong/agent-reach",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/Panniantong/Agent-Reach/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/Panniantong/Agent-Reach",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 7,
      "source_rank": 7,
      "source_scope": "weekly:all",
      "previous_rank": 8,
      "rank_delta": 1,
      "trend": "up",
      "importance": "general",
      "description": "Panniantong/Agent-Reach 本周出现在开源榜单 weekly #7，本周 +7,199 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "interviewstreet/hiring-agent",
      "repo": "interviewstreet/hiring-agent",
      "readme_cache": {
        "key": "github-readme/interviewstreet/hiring-agent/main/unknown",
        "hit": true,
        "repo": "interviewstreet/hiring-agent",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/interviewstreet/hiring-agent/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/interviewstreet/hiring-agent",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 8,
      "source_rank": 8,
      "source_scope": "weekly:all",
      "previous_rank": 16,
      "rank_delta": 8,
      "trend": "up",
      "importance": "general",
      "description": "interviewstreet/hiring-agent 本周出现在开源榜单 weekly #8，本周 +1,727 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "JCodesMore/ai-website-cloner-template",
      "repo": "JCodesMore/ai-website-cloner-template",
      "readme_cache": {
        "key": "github-readme/jcodesmore/ai-website-cloner-template/master/unknown",
        "hit": true,
        "repo": "jcodesmore/ai-website-cloner-template",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/JCodesMore/ai-website-cloner-template/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/JCodesMore/ai-website-cloner-template",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 9,
      "source_rank": 9,
      "source_scope": "weekly:all",
      "previous_rank": 12,
      "rank_delta": 3,
      "trend": "up",
      "importance": "general",
      "description": "ai-website-cloner-template 是代理式自动化、工具调用和开发者工作流相关的开源项目，公开说明提到Agent 构建等能力，并提供示例；评估时核对安装步骤、许可证、示例质量、近期维护和接入边界。 它把相关能力沉淀为代码、示例和集成入口，方便和同类方案做功能与工程成本比较。"
    },
    {
      "name": "jamiepine/voicebox",
      "repo": "jamiepine/voicebox",
      "readme_cache": {
        "key": "github-readme/jamiepine/voicebox/main/unknown",
        "hit": true,
        "repo": "jamiepine/voicebox",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/jamiepine/voicebox/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/jamiepine/voicebox",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 10,
      "source_rank": 10,
      "source_scope": "weekly:all",
      "previous_rank": 6,
      "rank_delta": -4,
      "trend": "down",
      "importance": "general",
      "description": "voicebox 是代理式自动化、工具调用和开发者工作流相关的开源项目，公开说明提到Agent 构建、API/SDK 适配等能力，并提供示例；评估时核对安装步骤、许可证、示例质量、近期维护和接入边界。 它把相关能力沉淀为代码、示例和集成入口，方便和同类方案做功能与工程成本比较。"
    },
    {
      "name": "NVIDIA/SkillSpector",
      "repo": "NVIDIA/SkillSpector",
      "readme_cache": {
        "key": "github-readme/nvidia/skillspector/main/unknown",
        "hit": true,
        "repo": "nvidia/skillspector",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/NVIDIA/SkillSpector/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/NVIDIA/SkillSpector",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Python weekly",
      "language": "python",
      "window": "weekly",
      "rank": 11,
      "source_rank": 9,
      "source_scope": "weekly:python",
      "previous_rank": 11,
      "rank_delta": 2,
      "trend": "up",
      "importance": "general",
      "description": "NVIDIA/SkillSpector 本周出现在开源榜单 Python weekly #11，本周 +2,752 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "iptv-org/iptv",
      "repo": "iptv-org/iptv",
      "readme_cache": {
        "key": "github-readme/iptv-org/iptv/master/unknown",
        "hit": true,
        "repo": "iptv-org/iptv",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/iptv-org/iptv/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/iptv-org/iptv",
      "event_date": "2026-06-28",
      "source": "GitHub Trending TypeScript weekly",
      "language": "typescript",
      "window": "weekly",
      "rank": 12,
      "source_rank": 8,
      "source_scope": "weekly:typescript",
      "previous_rank": 14,
      "rank_delta": 6,
      "trend": "up",
      "importance": "general",
      "description": "iptv-org/iptv 本周出现在开源榜单 TypeScript weekly #12，本周 +3,054 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "tursodatabase/turso",
      "repo": "tursodatabase/turso",
      "readme_cache": {
        "key": "github-readme/tursodatabase/turso/main/unknown",
        "hit": true,
        "repo": "tursodatabase/turso",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/tursodatabase/turso/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/tursodatabase/turso",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Rust weekly",
      "language": "rust",
      "window": "weekly",
      "rank": 13,
      "source_rank": 1,
      "source_scope": "weekly:rust",
      "previous_rank": 4,
      "rank_delta": 3,
      "trend": "up",
      "importance": "general",
      "description": "turso 是AI 工程实践相关的开源项目，公开说明提到项目框架、示例代码和可复用工具链等能力，并提供部署说明；评估时核对安装步骤、许可证、示例质量、近期维护和接入边界。 它把相关能力沉淀为代码、示例和集成入口，方便和同类方案做功能与工程成本比较。"
    },
    {
      "name": "Tencent/WeKnora",
      "repo": "Tencent/WeKnora",
      "readme_cache": {
        "key": "github-readme/tencent/weknora/main/unknown",
        "hit": true,
        "repo": "tencent/weknora",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/Tencent/WeKnora/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/Tencent/WeKnora",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Go weekly",
      "language": "go",
      "window": "weekly",
      "rank": 14,
      "source_rank": 2,
      "source_scope": "weekly:go",
      "previous_rank": 14,
      "rank_delta": 12,
      "trend": "up",
      "importance": "general",
      "description": "Tencent/WeKnora 本周出现在开源榜单 Go weekly #14，本周 +918 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "GeyserMC/Geyser",
      "repo": "GeyserMC/Geyser",
      "readme_cache": {
        "key": "github-readme/geysermc/geyser/master/unknown",
        "hit": true,
        "repo": "geysermc/geyser",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/GeyserMC/Geyser/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/GeyserMC/Geyser",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Java weekly",
      "language": "java",
      "window": "weekly",
      "rank": 15,
      "source_rank": 2,
      "source_scope": "weekly:java",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "GeyserMC/Geyser 本周出现在开源榜单 Java weekly #15，本周 +26 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "NanmiCoder/MediaCrawler",
      "repo": "NanmiCoder/MediaCrawler",
      "readme_cache": {
        "key": "github-readme/nanmicoder/mediacrawler/main/unknown",
        "hit": true,
        "repo": "nanmicoder/mediacrawler",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/NanmiCoder/MediaCrawler/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/NanmiCoder/MediaCrawler",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Python weekly",
      "language": "python",
      "window": "weekly",
      "rank": 16,
      "source_rank": 10,
      "source_scope": "weekly:python",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "NanmiCoder/MediaCrawler 本周出现在开源榜单 Python weekly #16，本周 +1,897 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "Kong/insomnia",
      "repo": "Kong/insomnia",
      "readme_cache": {
        "key": "github-readme/kong/insomnia/master/unknown",
        "hit": true,
        "repo": "kong/insomnia",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/Kong/insomnia/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/Kong/insomnia",
      "event_date": "2026-06-28",
      "source": "GitHub Trending TypeScript weekly",
      "language": "typescript",
      "window": "weekly",
      "rank": 17,
      "source_rank": 9,
      "source_scope": "weekly:typescript",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "Kong/insomnia 本周出现在开源榜单 TypeScript weekly #17，本周 +981 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "googleworkspace/cli",
      "repo": "googleworkspace/cli",
      "readme_cache": {
        "key": "github-readme/googleworkspace/cli/main/unknown",
        "hit": true,
        "repo": "googleworkspace/cli",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/googleworkspace/cli/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/googleworkspace/cli",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Rust weekly",
      "language": "rust",
      "window": "weekly",
      "rank": 18,
      "source_rank": 2,
      "source_scope": "weekly:rust",
      "previous_rank": 18,
      "rank_delta": 16,
      "trend": "up",
      "importance": "general",
      "description": "googleworkspace/cli 本周出现在开源榜单 Rust weekly #18，本周 +1,720 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "junegunn/fzf",
      "repo": "junegunn/fzf",
      "readme_cache": {
        "key": "github-readme/junegunn/fzf/master/unknown",
        "hit": true,
        "repo": "junegunn/fzf",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/junegunn/fzf/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/junegunn/fzf",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Go weekly",
      "language": "go",
      "window": "weekly",
      "rank": 19,
      "source_rank": 3,
      "source_scope": "weekly:go",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "junegunn/fzf 本周出现在开源榜单 Go weekly #19，本周 +271 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    },
    {
      "name": "ashishps1/awesome-low-level-design",
      "repo": "ashishps1/awesome-low-level-design",
      "readme_cache": {
        "key": "github-readme/ashishps1/awesome-low-level-design/main/unknown",
        "hit": true,
        "repo": "ashishps1/awesome-low-level-design",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/ashishps1/awesome-low-level-design/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/ashishps1/awesome-low-level-design",
      "event_date": "2026-06-28",
      "source": "GitHub Trending Java weekly",
      "language": "java",
      "window": "weekly",
      "rank": 20,
      "source_rank": 3,
      "source_scope": "weekly:java",
      "previous_rank": 6,
      "rank_delta": 3,
      "trend": "up",
      "importance": "general",
      "description": "ashishps1/awesome-low-level-design 本周出现在开源榜单 Java weekly #20，本周 +211 stars；当前只能确认榜单动量，正式采用前还要核对 README、许可证、维护状态和 issue 反馈。"
    }
  ],
  "huggingface_trending": [
    {
      "name": "deepseek-ai/DeepSeek-R1",
      "repo": "deepseek-ai/DeepSeek-R1",
      "description": "deepseek-ai/DeepSeek-R1 是 Hugging Face 上的文本生成模型，可作为文本生成或推理基线候选；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-R1",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-generation",
      "downloads": 7292805,
      "likes": 13416,
      "rank": 1,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "notable"
    },
    {
      "name": "black-forest-labs/FLUX.1-dev",
      "repo": "black-forest-labs/FLUX.1-dev",
      "description": "black-forest-labs/FLUX.1-dev 是 Hugging Face 上的图像生成模型，适合关注图像生成工作流的模型对比；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/black-forest-labs/FLUX.1-dev",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-to-image",
      "downloads": 1104100,
      "likes": 13375,
      "rank": 2,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "notable"
    },
    {
      "name": "stabilityai/stable-diffusion-xl-base-1.0",
      "repo": "stabilityai/stable-diffusion-xl-base-1.0",
      "description": "stabilityai/stable-diffusion-xl-base-1.0 是 Hugging Face 上的图像生成模型，适合关注图像生成工作流的模型对比；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-to-image",
      "downloads": 1343532,
      "likes": 7861,
      "rank": 3,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "notable"
    },
    {
      "name": "CompVis/stable-diffusion-v1-4",
      "repo": "CompVis/stable-diffusion-v1-4",
      "description": "CompVis/stable-diffusion-v1-4 是 Hugging Face 上的图像生成模型，适合关注图像生成工作流的模型对比；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/CompVis/stable-diffusion-v1-4",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-to-image",
      "downloads": 436720,
      "likes": 7026,
      "rank": 4,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    },
    {
      "name": "meta-llama/Meta-Llama-3-8B",
      "repo": "meta-llama/Meta-Llama-3-8B",
      "description": "meta-llama/Meta-Llama-3-8B 是 Hugging Face 上的文本生成模型，可作为文本生成或推理基线候选；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/meta-llama/Meta-Llama-3-8B",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-generation",
      "downloads": 1249942,
      "likes": 6586,
      "rank": 5,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    },
    {
      "name": "hexgrad/Kokoro-82M",
      "repo": "hexgrad/Kokoro-82M",
      "description": "hexgrad/Kokoro-82M 是 Hugging Face 上的语音或音频模型，适合关注语音和音频链路的模型对比；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/hexgrad/Kokoro-82M",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-to-speech",
      "downloads": 15754089,
      "likes": 6393,
      "rank": 6,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    },
    {
      "name": "meta-llama/Llama-3.1-8B-Instruct",
      "repo": "meta-llama/Llama-3.1-8B-Instruct",
      "description": "meta-llama/Llama-3.1-8B-Instruct 是 Hugging Face 上的文本生成模型，可作为文本生成或推理基线候选；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-generation",
      "downloads": 10147881,
      "likes": 6161,
      "rank": 7,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    },
    {
      "name": "openai/whisper-large-v3",
      "repo": "openai/whisper-large-v3",
      "description": "openai/whisper-large-v3 是 Hugging Face 上的语音或音频模型，适合关注语音和音频链路的模型对比；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/openai/whisper-large-v3",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "automatic-speech-recognition",
      "downloads": 5743363,
      "likes": 5881,
      "rank": 8,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    },
    {
      "name": "black-forest-labs/FLUX.1-schnell",
      "repo": "black-forest-labs/FLUX.1-schnell",
      "description": "black-forest-labs/FLUX.1-schnell 是 Hugging Face 上的图像生成模型，适合关注图像生成工作流的模型对比；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/black-forest-labs/FLUX.1-schnell",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-to-image",
      "downloads": 232031,
      "likes": 5225,
      "rank": 9,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    },
    {
      "name": "deepseek-ai/DeepSeek-V4-Pro",
      "repo": "deepseek-ai/DeepSeek-V4-Pro",
      "description": "deepseek-ai/DeepSeek-V4-Pro 是 Hugging Face 上的文本生成模型，可作为文本生成或推理基线候选；榜单数据只代表社区关注和调用热度，选型前仍要核对模型卡、许可证、限制和部署成本。",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "event_date": "2026-06-28",
      "source": "Hugging Face Trending Models",
      "task": "text-generation",
      "downloads": 1168421,
      "likes": 5084,
      "rank": 10,
      "trend": "trending",
      "editorial_category": "open_source",
      "importance": "general"
    }
  ],
  "model_releases": [],
  "hot_blogs": [
    {
      "title": "Google披露模型能力和推理入口变化",
      "editorial_category": "viewpoint_analysis",
      "image_url": "https://storage.googleapis.com/gweb-research2023-media/original_images/MTP1_Architecture.png",
      "image_alt": "Accelerating Gemini Nano models on Pixel with frozen Multi-Token Prediction",
      "image_source": "feed",
      "url": "https://research.google/blog/accelerating-gemini-nano-models-on-pixel-with-frozen-multi-token-prediction/",
      "publisher": "Google Research Blog",
      "author": "Google Research Blog",
      "event_date": "2026-06-26",
      "topic": "research / evaluation",
      "summary": "Google披露模型能力和评估方法更新，重点落在能力边界、评估设置、数据来源、使用场景和限制说明。更有价值的信息是模型能力、评估设置、数据来源和限制说明，判断这类方案时还要看结论仍要依赖可复现评测、真实任务和公开限制。文章梳理模型评测或研究结论怎样改变能力边界、成本预期和可靠性判断。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "相关团队更新AI 产品、平台或工程实践",
      "editorial_category": "viewpoint_analysis",
      "url": "https://huggingface.co/datasets/Anthropic/EconomicIndex",
      "publisher": "Anthropic Hugging Face Organization",
      "author": "Anthropic Hugging Face Organization",
      "event_date": "2026-06-26",
      "topic": "AI industry",
      "summary": "相关团队更新AI 产品、平台或工程实践，重点落在功能变化、使用场景、接入方式、限制条件和后续部署边界。更有价值的信息是功能变化、适用场景、接入方式和限制条件，判断这类方案时还要看公开材料仍需要回到原文核对入口、权限、价格和适用范围。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "相关团队披露模型能力和评估方法更新",
      "editorial_category": "viewpoint_analysis",
      "url": "https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2",
      "publisher": "Hugging Face Trending Models",
      "author": "Hugging Face Trending Models",
      "event_date": "2026-06-28",
      "topic": "AI industry",
      "summary": "相关团队披露模型能力和评估方法更新，重点落在能力边界、评估设置、数据来源、使用场景和限制说明。更有价值的信息是模型能力、评估设置、数据来源和限制说明，判断这类方案时还要看结论仍要依赖可复现评测、真实任务和公开限制。文章梳理一个 AI 产品、平台或工程实践的具体变化，而不是只给观点。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "NVIDIA披露模型权重和使用说明",
      "editorial_category": "viewpoint_analysis",
      "url": "https://developer.nvidia.com/blog/creating-the-nvidia-nemotron-3-ultra-nvfp4-checkpoint-with-nvidia-model-optimizer/",
      "publisher": "NVIDIA Developer Blog",
      "author": "NVIDIA Developer Blog",
      "event_date": "2026-06-26",
      "topic": "AI engineering tools",
      "summary": "NVIDIA更新agent 工作流和开发工具能力，重点落在任务编排、上下文、权限控制、工程集成和失败恢复。更有价值的信息是agent 工作流、开发工具入口、权限控制和工程集成，判断这类方案时还要看落地质量取决于权限模型、评估回放、团队流程和可观测性。文章拆解 agent、开发工具或自动化流程里的任务规划、权限、上下文、工具调用和失败恢复。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "GitHub Changelog披露 agent 与开发者工具能力",
      "editorial_category": "viewpoint_analysis",
      "url": "https://github.blog/changelog/2026-06-26-track-total-merges-by-adoption-phase-in-enterprise-and-organization-reports",
      "publisher": "GitHub Changelog",
      "author": "GitHub Changelog",
      "event_date": "2026-06-26",
      "topic": "AI industry",
      "summary": "该开源项目更新AI 产品、平台或工程实践，重点落在功能变化、使用场景、接入方式、限制条件和后续部署边界。更有价值的信息是功能变化、适用场景、接入方式和限制条件，判断这类方案时还要看公开材料仍需要回到原文核对入口、权限、价格和适用范围。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "该开源项目更新AI 产品、平台或工程实践",
      "editorial_category": "viewpoint_analysis",
      "url": "https://github.blog/changelog/2026-06-26-github-desktop-3-6-worktrees-and-deeper-copilot-integration",
      "publisher": "GitHub Changelog",
      "author": "GitHub Changelog",
      "event_date": "2026-06-26",
      "topic": "AI industry",
      "summary": "该开源项目更新AI 产品、平台或工程实践，重点落在功能变化、使用场景、接入方式、限制条件和后续部署边界。更有价值的信息是功能变化、适用场景、接入方式和限制条件，判断这类方案时还要看公开材料仍需要回到原文核对入口、权限、价格和适用范围。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "NVIDIA披露 agent 与开发者工具能力",
      "editorial_category": "viewpoint_analysis",
      "url": "https://developer.nvidia.com/blog/deploy-a-production-ready-nvidia-ai-q-blueprint-on-oracle-cloud-infrastructure/",
      "publisher": "NVIDIA Developer Blog",
      "author": "NVIDIA Developer Blog",
      "event_date": "2026-06-26",
      "topic": "AI engineering tools",
      "summary": "NVIDIA更新agent 工作流和开发工具能力，重点落在任务编排、上下文、权限控制、工程集成和失败恢复。更有价值的信息是agent 工作流、开发工具入口、权限控制和工程集成，判断这类方案时还要看落地质量取决于权限模型、评估回放、团队流程和可观测性。文章拆解 agent、开发工具或自动化流程里的任务规划、权限、上下文、工具调用和失败恢复。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "AWS更新AI 产品、平台或工程实践",
      "editorial_category": "viewpoint_analysis",
      "url": "https://aws.amazon.com/blogs/machine-learning/how-cara-pioneers-domain-specific-ai-for-enterprise-insurance-brokerages-with-aws/",
      "publisher": "AWS Machine Learning Blog",
      "author": "AWS Machine Learning Blog",
      "event_date": "2026-06-26",
      "topic": "AI industry",
      "summary": "AWS更新AI 产品、平台或工程实践，重点落在功能变化、使用场景、接入方式、限制条件和后续部署边界。更有价值的信息是功能变化、适用场景、接入方式和限制条件，判断这类方案时还要看公开材料仍需要回到原文核对入口、权限、价格和适用范围。文章梳理一个 AI 产品、平台或工程实践的具体变化，而不是只给观点。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    }
  ],
  "chinese_media_dynamics": [],
  "daily_tracking": [
    {
      "id": "openrouter-rankings",
      "name": "OpenRouter",
      "url": "https://openrouter.ai/rankings",
      "event_date": "2026-06-28",
      "source": "OpenRouter Rankings",
      "category": "model_usage",
      "importance": "notable",
      "change_status": "changed",
      "change_summary": "OpenRouter 本周 Top 10 已解析：#1 DeepSeek V4 Flash 4.83T tokens；#2 MiMo-V2.5 4.49T tokens；#3 MiniMax M3 3.83T tokens；GLM 5.2 周变化 123%。",
      "summary": "OpenRouter 公开榜单显示，本周调用热度第一是 DeepSeek V4 Flash（deepseek，4.83T tokens，周变化 3%）。 Top 10 供应商分布为 anthropic 3、deepseek 2、minimax 1、openrouter 1、tencent 1、xiaomi 1、z-ai 1，可用来观察开发者在 OpenRouter 平台内的真实调用偏好。 该快照只说明 OpenRouter 平台内使用热度，不能替代能力榜单或全市场份额判断。",
      "watch_points": [
        "GLM 5.2 的周变化为 123%，需要结合发布、价格、免费额度和上下文窗口变化判断原因。",
        "若没有新进榜，重点看榜首和供应商份额是否迁移。",
        "OpenRouter 用量是平台内需求信号；生产选型仍需回到延迟、价格、上下文长度和自有任务复测。"
      ],
      "metrics": [
        {
          "label": "榜单范围",
          "value": "This Week Top 10",
          "trend": "same"
        },
        {
          "label": "供应商分布",
          "value": "anthropic 3、deepseek 2、minimax 1、openrouter 1、tencent 1、xiaomi 1、z-ai 1",
          "trend": "unknown"
        },
        {
          "label": "#1",
          "value": "DeepSeek V4 Flash（deepseek）：4.83T tokens，周变化 3%",
          "trend": "up"
        },
        {
          "label": "#2",
          "value": "MiMo-V2.5（xiaomi）：4.49T tokens，周变化 17%",
          "trend": "up"
        },
        {
          "label": "#3",
          "value": "MiniMax M3（minimax）：3.83T tokens，周变化 7%",
          "trend": "up"
        },
        {
          "label": "#4",
          "value": "Owl Alpha（openrouter）：3.29T tokens，周变化 38%",
          "trend": "up"
        },
        {
          "label": "#5",
          "value": "Hy3 preview（tencent）：3.28T tokens，周变化 6%",
          "trend": "up"
        },
        {
          "label": "#6",
          "value": "Claude Opus 4.7（anthropic）：2.34T tokens，周变化 20%",
          "trend": "up"
        },
        {
          "label": "#7",
          "value": "DeepSeek V4 Pro（deepseek）：2.07T tokens，周变化 17%",
          "trend": "up"
        },
        {
          "label": "#8",
          "value": "Claude Opus 4.8（anthropic）：2.06T tokens，周变化 47%",
          "trend": "up"
        },
        {
          "label": "#9",
          "value": "GLM 5.2（z-ai）：1.92T tokens，周变化 123%",
          "trend": "up"
        },
        {
          "label": "#10",
          "value": "Claude Sonnet 4.6（anthropic）：1.49T tokens，周变化 4%",
          "trend": "up"
        }
      ],
      "snapshot": {
        "type": "openrouter_rankings_public_page",
        "collection_method": "public_page_playwright",
        "snapshot_status": "complete",
        "snapshot_as_of": "2026-06-27T18:34:22.805Z",
        "source_url": "https://openrouter.ai/rankings",
        "top_entries": [
          {
            "rank": 1,
            "model": "DeepSeek V4 Flash",
            "provider": "deepseek",
            "tokens": "4.83T tokens",
            "change": "3%"
          },
          {
            "rank": 2,
            "model": "MiMo-V2.5",
            "provider": "xiaomi",
            "tokens": "4.49T tokens",
            "change": "17%"
          },
          {
            "rank": 3,
            "model": "MiniMax M3",
            "provider": "minimax",
            "tokens": "3.83T tokens",
            "change": "7%"
          },
          {
            "rank": 4,
            "model": "Owl Alpha",
            "provider": "openrouter",
            "tokens": "3.29T tokens",
            "change": "38%"
          },
          {
            "rank": 5,
            "model": "Hy3 preview",
            "provider": "tencent",
            "tokens": "3.28T tokens",
            "change": "6%"
          },
          {
            "rank": 6,
            "model": "Claude Opus 4.7",
            "provider": "anthropic",
            "tokens": "2.34T tokens",
            "change": "20%"
          },
          {
            "rank": 7,
            "model": "DeepSeek V4 Pro",
            "provider": "deepseek",
            "tokens": "2.07T tokens",
            "change": "17%"
          },
          {
            "rank": 8,
            "model": "Claude Opus 4.8",
            "provider": "anthropic",
            "tokens": "2.06T tokens",
            "change": "47%"
          },
          {
            "rank": 9,
            "model": "GLM 5.2",
            "provider": "z-ai",
            "tokens": "1.92T tokens",
            "change": "123%"
          },
          {
            "rank": 10,
            "model": "Claude Sonnet 4.6",
            "provider": "anthropic",
            "tokens": "1.49T tokens",
            "change": "4%"
          }
        ],
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "openrouter_rankings",
          "source_url": "https://openrouter.ai/rankings",
          "captured_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "openrouter-rankings-v1",
          "source_selector": "[data-openrouter-rankings]",
          "sanitized_html": "<section class=\"openrouter-rankings-card\" data-openrouter-rankings>\n        <header>\n          <p>OpenRouter Top Models</p>\n          <span>This Week usage ranking</span>\n        </header>\n        <table>\n          <thead><tr><th>Rank</th><th>Model</th><th>Provider</th><th>Tokens</th><th>Change</th></tr></thead>\n          <tbody>\n        <tr><td>#1</td><td>DeepSeek V4 Flash</td><td>deepseek</td><td>4.83T tokens</td><td>3%</td></tr>\n        <tr><td>#2</td><td>MiMo-V2.5</td><td>xiaomi</td><td>4.49T tokens</td><td>17%</td></tr>\n        <tr><td>#3</td><td>MiniMax M3</td><td>minimax</td><td>3.83T tokens</td><td>7%</td></tr>\n        <tr><td>#4</td><td>Owl Alpha</td><td>openrouter</td><td>3.29T tokens</td><td>38%</td></tr>\n        <tr><td>#5</td><td>Hy3 preview</td><td>tencent</td><td>3.28T tokens</td><td>6%</td></tr>\n        <tr><td>#6</td><td>Claude Opus 4.7</td><td>anthropic</td><td>2.34T tokens</td><td>20%</td></tr>\n        <tr><td>#7</td><td>DeepSeek V4 Pro</td><td>deepseek</td><td>2.07T tokens</td><td>17%</td></tr>\n        <tr><td>#8</td><td>Claude Opus 4.8</td><td>anthropic</td><td>2.06T tokens</td><td>47%</td></tr>\n        <tr><td>#9</td><td>GLM 5.2</td><td>z-ai</td><td>1.92T tokens</td><td>123%</td></tr>\n        <tr><td>#10</td><td>Claude Sonnet 4.6</td><td>anthropic</td><td>1.49T tokens</td><td>4%</td></tr></tbody>\n        </table>\n      </section>",
          "sanitized_css": ".openrouter-rankings-card { border: 1px solid currentColor; padding: 16px; }\n      .openrouter-rankings-card table { width: 100%; border-collapse: collapse; }\n      .openrouter-rankings-card th, .openrouter-rankings-card td { padding: 8px; border-top: 1px solid currentColor; text-align: left; }",
          "dom_hash": "sha256:e7896dbf7fc5f2e4bb89204ccd9c7c37674308335f5153f4b044f0f859b9a267",
          "css_hash": "sha256:e5df3dc0e07de42f5c2ca4021bbf59258d47d1ef0fa569d55d98b09876618e43"
        },
        "history_entries": []
      },
      "tracking_component_snapshot": {
        "source": "OpenRouter",
        "component_kind": "openrouter_rankings",
        "source_url": "https://openrouter.ai/rankings",
        "collected_at": "2026-06-27T18:34:22.805Z",
        "selector_version": "openrouter-rankings-v1",
        "raw_dom_hash": "sha256:f625a4ac064b947f5ab56230694d91fe4be8989c68b6e1fbfc4856aa2c047ccc",
        "data_hash": "sha256:38e42a2a3f933e4349214b7048e39d3cc996c3d33dcf4f5c0b53747a75a32165",
        "tabs": [
          {
            "id": "top-models",
            "label": "Top Models",
            "view": "stacked_bar",
            "fallback_reason": ""
          },
          {
            "id": "leaderboard",
            "label": "LLM Leaderboard",
            "view": "leaderboard",
            "fallback_reason": ""
          }
        ],
        "series": [
          {
            "id": "openrouter-top-models-weekly-usage",
            "tab_id": "top-models",
            "label": "Weekly usage across OpenRouter",
            "chart": "stacked_bar",
            "rows": [
              {
                "rank": 1,
                "model": "DeepSeek V4 Flash",
                "provider": "deepseek",
                "value": 4830000000000,
                "value_label": "4.83T tokens",
                "change": "3%"
              },
              {
                "rank": 2,
                "model": "MiMo-V2.5",
                "provider": "xiaomi",
                "value": 4490000000000,
                "value_label": "4.49T tokens",
                "change": "17%"
              },
              {
                "rank": 3,
                "model": "MiniMax M3",
                "provider": "minimax",
                "value": 3830000000000,
                "value_label": "3.83T tokens",
                "change": "7%"
              },
              {
                "rank": 4,
                "model": "Owl Alpha",
                "provider": "openrouter",
                "value": 3290000000000,
                "value_label": "3.29T tokens",
                "change": "38%"
              },
              {
                "rank": 5,
                "model": "Hy3 preview",
                "provider": "tencent",
                "value": 3280000000000,
                "value_label": "3.28T tokens",
                "change": "6%"
              },
              {
                "rank": 6,
                "model": "Claude Opus 4.7",
                "provider": "anthropic",
                "value": 2340000000000,
                "value_label": "2.34T tokens",
                "change": "20%"
              },
              {
                "rank": 7,
                "model": "DeepSeek V4 Pro",
                "provider": "deepseek",
                "value": 2069999999999.9998,
                "value_label": "2.07T tokens",
                "change": "17%"
              },
              {
                "rank": 8,
                "model": "Claude Opus 4.8",
                "provider": "anthropic",
                "value": 2060000000000,
                "value_label": "2.06T tokens",
                "change": "47%"
              },
              {
                "rank": 9,
                "model": "GLM 5.2",
                "provider": "z-ai",
                "value": 1920000000000,
                "value_label": "1.92T tokens",
                "change": "123%"
              },
              {
                "rank": 10,
                "model": "Claude Sonnet 4.6",
                "provider": "anthropic",
                "value": 1490000000000,
                "value_label": "1.49T tokens",
                "change": "4%"
              }
            ],
            "fallback_reason": ""
          },
          {
            "id": "openrouter-llm-leaderboard",
            "tab_id": "leaderboard",
            "label": "LLM Leaderboard",
            "chart": "leaderboard",
            "rows": [
              {
                "rank": 1,
                "model": "DeepSeek V4 Flash",
                "provider": "deepseek",
                "value": 4830000000000,
                "value_label": "4.83T tokens",
                "change": "3%"
              },
              {
                "rank": 2,
                "model": "MiMo-V2.5",
                "provider": "xiaomi",
                "value": 4490000000000,
                "value_label": "4.49T tokens",
                "change": "17%"
              },
              {
                "rank": 3,
                "model": "MiniMax M3",
                "provider": "minimax",
                "value": 3830000000000,
                "value_label": "3.83T tokens",
                "change": "7%"
              },
              {
                "rank": 4,
                "model": "Owl Alpha",
                "provider": "openrouter",
                "value": 3290000000000,
                "value_label": "3.29T tokens",
                "change": "38%"
              },
              {
                "rank": 5,
                "model": "Hy3 preview",
                "provider": "tencent",
                "value": 3280000000000,
                "value_label": "3.28T tokens",
                "change": "6%"
              },
              {
                "rank": 6,
                "model": "Claude Opus 4.7",
                "provider": "anthropic",
                "value": 2340000000000,
                "value_label": "2.34T tokens",
                "change": "20%"
              },
              {
                "rank": 7,
                "model": "DeepSeek V4 Pro",
                "provider": "deepseek",
                "value": 2069999999999.9998,
                "value_label": "2.07T tokens",
                "change": "17%"
              },
              {
                "rank": 8,
                "model": "Claude Opus 4.8",
                "provider": "anthropic",
                "value": 2060000000000,
                "value_label": "2.06T tokens",
                "change": "47%"
              },
              {
                "rank": 9,
                "model": "GLM 5.2",
                "provider": "z-ai",
                "value": 1920000000000,
                "value_label": "1.92T tokens",
                "change": "123%"
              },
              {
                "rank": 10,
                "model": "Claude Sonnet 4.6",
                "provider": "anthropic",
                "value": 1490000000000,
                "value_label": "1.49T tokens",
                "change": "4%"
              }
            ],
            "fallback_reason": ""
          }
        ],
        "rows": [
          {
            "rank": 1,
            "model": "DeepSeek V4 Flash",
            "provider": "deepseek",
            "value": 4830000000000,
            "value_label": "4.83T tokens",
            "change": "3%"
          },
          {
            "rank": 2,
            "model": "MiMo-V2.5",
            "provider": "xiaomi",
            "value": 4490000000000,
            "value_label": "4.49T tokens",
            "change": "17%"
          },
          {
            "rank": 3,
            "model": "MiniMax M3",
            "provider": "minimax",
            "value": 3830000000000,
            "value_label": "3.83T tokens",
            "change": "7%"
          },
          {
            "rank": 4,
            "model": "Owl Alpha",
            "provider": "openrouter",
            "value": 3290000000000,
            "value_label": "3.29T tokens",
            "change": "38%"
          },
          {
            "rank": 5,
            "model": "Hy3 preview",
            "provider": "tencent",
            "value": 3280000000000,
            "value_label": "3.28T tokens",
            "change": "6%"
          },
          {
            "rank": 6,
            "model": "Claude Opus 4.7",
            "provider": "anthropic",
            "value": 2340000000000,
            "value_label": "2.34T tokens",
            "change": "20%"
          },
          {
            "rank": 7,
            "model": "DeepSeek V4 Pro",
            "provider": "deepseek",
            "value": 2069999999999.9998,
            "value_label": "2.07T tokens",
            "change": "17%"
          },
          {
            "rank": 8,
            "model": "Claude Opus 4.8",
            "provider": "anthropic",
            "value": 2060000000000,
            "value_label": "2.06T tokens",
            "change": "47%"
          },
          {
            "rank": 9,
            "model": "GLM 5.2",
            "provider": "z-ai",
            "value": 1920000000000,
            "value_label": "1.92T tokens",
            "change": "123%"
          },
          {
            "rank": 10,
            "model": "Claude Sonnet 4.6",
            "provider": "anthropic",
            "value": 1490000000000,
            "value_label": "1.49T tokens",
            "change": "4%"
          }
        ],
        "previous_snapshot": null,
        "diff": {
          "summary": "No previous component snapshot was available for comparison.",
          "changed_rows": [],
          "new_entries": [
            "DeepSeek V4 Flash",
            "MiMo-V2.5",
            "MiniMax M3",
            "Owl Alpha",
            "Hy3 preview",
            "Claude Opus 4.7",
            "DeepSeek V4 Pro",
            "Claude Opus 4.8",
            "GLM 5.2",
            "Claude Sonnet 4.6"
          ]
        },
        "cache_path": "",
        "fallback_reason": "",
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "openrouter_rankings",
          "source_url": "https://openrouter.ai/rankings",
          "captured_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "openrouter-rankings-v1",
          "source_selector": "[data-openrouter-rankings]",
          "sanitized_html": "<section class=\"openrouter-rankings-card\" data-openrouter-rankings>\n        <header>\n          <p>OpenRouter Top Models</p>\n          <span>This Week usage ranking</span>\n        </header>\n        <table>\n          <thead><tr><th>Rank</th><th>Model</th><th>Provider</th><th>Tokens</th><th>Change</th></tr></thead>\n          <tbody>\n        <tr><td>#1</td><td>DeepSeek V4 Flash</td><td>deepseek</td><td>4.83T tokens</td><td>3%</td></tr>\n        <tr><td>#2</td><td>MiMo-V2.5</td><td>xiaomi</td><td>4.49T tokens</td><td>17%</td></tr>\n        <tr><td>#3</td><td>MiniMax M3</td><td>minimax</td><td>3.83T tokens</td><td>7%</td></tr>\n        <tr><td>#4</td><td>Owl Alpha</td><td>openrouter</td><td>3.29T tokens</td><td>38%</td></tr>\n        <tr><td>#5</td><td>Hy3 preview</td><td>tencent</td><td>3.28T tokens</td><td>6%</td></tr>\n        <tr><td>#6</td><td>Claude Opus 4.7</td><td>anthropic</td><td>2.34T tokens</td><td>20%</td></tr>\n        <tr><td>#7</td><td>DeepSeek V4 Pro</td><td>deepseek</td><td>2.07T tokens</td><td>17%</td></tr>\n        <tr><td>#8</td><td>Claude Opus 4.8</td><td>anthropic</td><td>2.06T tokens</td><td>47%</td></tr>\n        <tr><td>#9</td><td>GLM 5.2</td><td>z-ai</td><td>1.92T tokens</td><td>123%</td></tr>\n        <tr><td>#10</td><td>Claude Sonnet 4.6</td><td>anthropic</td><td>1.49T tokens</td><td>4%</td></tr></tbody>\n        </table>\n      </section>",
          "sanitized_css": ".openrouter-rankings-card { border: 1px solid currentColor; padding: 16px; }\n      .openrouter-rankings-card table { width: 100%; border-collapse: collapse; }\n      .openrouter-rankings-card th, .openrouter-rankings-card td { padding: 8px; border-top: 1px solid currentColor; text-align: left; }",
          "dom_hash": "sha256:e7896dbf7fc5f2e4bb89204ccd9c7c37674308335f5153f4b044f0f859b9a267",
          "css_hash": "sha256:e5df3dc0e07de42f5c2ca4021bbf59258d47d1ef0fa569d55d98b09876618e43"
        },
        "public_trace": {
          "source_url": "https://openrouter.ai/rankings",
          "collected_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "openrouter-rankings-v1",
          "data_hash": "sha256:38e42a2a3f933e4349214b7048e39d3cc996c3d33dcf4f5c0b53747a75a32165",
          "top_rows": [
            {
              "rank": 1,
              "model": "DeepSeek V4 Flash",
              "provider": "deepseek",
              "value_label": "4.83T tokens",
              "change": "3%"
            },
            {
              "rank": 2,
              "model": "MiMo-V2.5",
              "provider": "xiaomi",
              "value_label": "4.49T tokens",
              "change": "17%"
            },
            {
              "rank": 3,
              "model": "MiniMax M3",
              "provider": "minimax",
              "value_label": "3.83T tokens",
              "change": "7%"
            },
            {
              "rank": 4,
              "model": "Owl Alpha",
              "provider": "openrouter",
              "value_label": "3.29T tokens",
              "change": "38%"
            },
            {
              "rank": 5,
              "model": "Hy3 preview",
              "provider": "tencent",
              "value_label": "3.28T tokens",
              "change": "6%"
            },
            {
              "rank": 6,
              "model": "Claude Opus 4.7",
              "provider": "anthropic",
              "value_label": "2.34T tokens",
              "change": "20%"
            },
            {
              "rank": 7,
              "model": "DeepSeek V4 Pro",
              "provider": "deepseek",
              "value_label": "2.07T tokens",
              "change": "17%"
            },
            {
              "rank": 8,
              "model": "Claude Opus 4.8",
              "provider": "anthropic",
              "value_label": "2.06T tokens",
              "change": "47%"
            },
            {
              "rank": 9,
              "model": "GLM 5.2",
              "provider": "z-ai",
              "value_label": "1.92T tokens",
              "change": "123%"
            },
            {
              "rank": 10,
              "model": "Claude Sonnet 4.6",
              "provider": "anthropic",
              "value_label": "1.49T tokens",
              "change": "4%"
            }
          ],
          "diff": {
            "summary": "No previous component snapshot was available for comparison.",
            "changed_rows": [],
            "new_entries": [
              "DeepSeek V4 Flash",
              "MiMo-V2.5",
              "MiniMax M3",
              "Owl Alpha",
              "Hy3 preview",
              "Claude Opus 4.7",
              "DeepSeek V4 Pro",
              "Claude Opus 4.8",
              "GLM 5.2",
              "Claude Sonnet 4.6"
            ]
          },
          "cache_status": "live",
          "fallback_reason": ""
        }
      }
    },
    {
      "id": "artificial-analysis-intelligence-index",
      "name": "Artificial Analysis",
      "url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index",
      "event_date": "2026-06-28",
      "source": "Artificial Analysis Intelligence Index",
      "category": "model_benchmark",
      "importance": "notable",
      "change_status": "changed",
      "change_summary": "Artificial Analysis Intelligence Index Top 10 已解析：#1 Claude Fable 5 (with fallback) 60 分，#2 Claude Opus 4.8 (max) 56 分，#3 GPT-5.5 (xhigh) 55 分。",
      "summary": "Artificial Analysis 公开榜单显示，当前 Intelligence Index 第一是 Claude Fable 5 (with fallback)（anthropic，60 分）。 前三名为 Claude Fable 5 (with fallback) 60 分、Claude Opus 4.8 (max) 56 分、GPT-5.5 (xhigh) 55 分，Top 10 供应商分布为 anthropic 4、google 2、openai 2、alibaba 1、zhipu 1。 这个榜单适合做模型 shortlist 和能力变化监测，但生产选型仍要结合延迟、价格、上下文长度和自有任务复测。",
      "watch_points": [
        "榜首 Claude Fable 5 (with fallback) 的综合分为 60 分，需要继续看它在代码、长上下文和 agentic task 分项上的表现。",
        "Top 10 内部竞争接近：46 分有 2 个模型，不要只按一个名次做选型。",
        "把 Intelligence Index 与价格、延迟、吞吐和可用地区一起看，避免用综合分替代真实 workload 复测。"
      ],
      "metrics": [
        {
          "label": "榜单范围",
          "value": "Intelligence Index Top 10",
          "trend": "same"
        },
        {
          "label": "供应商分布",
          "value": "anthropic 4、google 2、openai 2、alibaba 1、zhipu 1",
          "trend": "unknown"
        },
        {
          "label": "#1",
          "value": "Claude Fable 5 (with fallback)（anthropic）：60 分",
          "trend": "unknown"
        },
        {
          "label": "#2",
          "value": "Claude Opus 4.8 (max)（anthropic）：56 分",
          "trend": "unknown"
        },
        {
          "label": "#3",
          "value": "GPT-5.5 (xhigh)（openai）：55 分",
          "trend": "unknown"
        },
        {
          "label": "#4",
          "value": "Claude Opus 4.7 (max)（anthropic）：54 分",
          "trend": "unknown"
        },
        {
          "label": "#5",
          "value": "GPT-5.5 (high)（openai）：53 分",
          "trend": "unknown"
        },
        {
          "label": "#6",
          "value": "GLM-5.2 (max)（zhipu）：51 分",
          "trend": "unknown"
        },
        {
          "label": "#7",
          "value": "Gemini 3.5 Flash（google）：50 分",
          "trend": "unknown"
        },
        {
          "label": "#8",
          "value": "Claude Sonnet 4.6 (max)（anthropic）：47 分",
          "trend": "unknown"
        },
        {
          "label": "#9",
          "value": "Gemini 3.1 Pro Preview（google）：46 分",
          "trend": "unknown"
        },
        {
          "label": "#10",
          "value": "Qwen3.7 Max（alibaba）：46 分",
          "trend": "unknown"
        }
      ],
      "snapshot": {
        "type": "artificial_analysis_intelligence_index_public_page",
        "collection_method": "public_page_playwright",
        "snapshot_status": "complete",
        "snapshot_as_of": "2026-06-27T18:34:22.805Z",
        "source_url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index",
        "top_entries": [
          {
            "rank": 1,
            "model": "Claude Fable 5 (with fallback)",
            "provider": "anthropic",
            "tokens": "60 分",
            "change": "AA Index"
          },
          {
            "rank": 2,
            "model": "Claude Opus 4.8 (max)",
            "provider": "anthropic",
            "tokens": "56 分",
            "change": "AA Index"
          },
          {
            "rank": 3,
            "model": "GPT-5.5 (xhigh)",
            "provider": "openai",
            "tokens": "55 分",
            "change": "AA Index"
          },
          {
            "rank": 4,
            "model": "Claude Opus 4.7 (max)",
            "provider": "anthropic",
            "tokens": "54 分",
            "change": "AA Index"
          },
          {
            "rank": 5,
            "model": "GPT-5.5 (high)",
            "provider": "openai",
            "tokens": "53 分",
            "change": "AA Index"
          },
          {
            "rank": 6,
            "model": "GLM-5.2 (max)",
            "provider": "zhipu",
            "tokens": "51 分",
            "change": "AA Index"
          },
          {
            "rank": 7,
            "model": "Gemini 3.5 Flash",
            "provider": "google",
            "tokens": "50 分",
            "change": "AA Index"
          },
          {
            "rank": 8,
            "model": "Claude Sonnet 4.6 (max)",
            "provider": "anthropic",
            "tokens": "47 分",
            "change": "AA Index"
          },
          {
            "rank": 9,
            "model": "Gemini 3.1 Pro Preview",
            "provider": "google",
            "tokens": "46 分",
            "change": "AA Index"
          },
          {
            "rank": 10,
            "model": "Qwen3.7 Max",
            "provider": "alibaba",
            "tokens": "46 分",
            "change": "AA Index"
          }
        ],
        "component_tabs": {
          "score": {
            "rows": [
              {
                "rank": 1,
                "model": "Claude Fable 5 (with fallback)",
                "provider": "anthropic",
                "value": 60,
                "value_label": "60 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 2,
                "model": "Claude Opus 4.8 (max)",
                "provider": "anthropic",
                "value": 56,
                "value_label": "56 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 3,
                "model": "GPT-5.5 (xhigh)",
                "provider": "openai",
                "value": 55,
                "value_label": "55 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 4,
                "model": "Claude Opus 4.7 (max)",
                "provider": "anthropic",
                "value": 54,
                "value_label": "54 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 5,
                "model": "GPT-5.5 (high)",
                "provider": "openai",
                "value": 53,
                "value_label": "53 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 6,
                "model": "GLM-5.2 (max)",
                "provider": "zhipu",
                "value": 51,
                "value_label": "51 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 7,
                "model": "Gemini 3.5 Flash",
                "provider": "google",
                "value": 50,
                "value_label": "50 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 8,
                "model": "Claude Sonnet 4.6 (max)",
                "provider": "anthropic",
                "value": 47,
                "value_label": "47 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 9,
                "model": "Gemini 3.1 Pro Preview",
                "provider": "google",
                "value": 46,
                "value_label": "46 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 10,
                "model": "Qwen3.7 Max",
                "provider": "alibaba",
                "value": 46,
                "value_label": "46 分",
                "change": "AA Index",
                "metric": "Score"
              }
            ]
          }
        },
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "artificial_analysis_index",
          "source_url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index",
          "captured_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "artificial-analysis-index-v1",
          "source_selector": "[data-artificial-analysis-index]",
          "sanitized_html": "<section class=\"artificial-analysis-index-card\" data-artificial-analysis-index>\n        <header>\n          <p>Artificial Analysis Intelligence Index</p>\n          <span>Top models by independent Intelligence Index</span>\n        </header>\n        <table>\n          <thead><tr><th>Rank</th><th>Model</th><th>Provider</th><th>Score</th><th>Metric</th></tr></thead>\n          <tbody>\n        <tr><td>#1</td><td>Claude Fable 5 (with fallback)</td><td>anthropic</td><td>60 分</td><td>AA Index</td></tr>\n        <tr><td>#2</td><td>Claude Opus 4.8 (max)</td><td>anthropic</td><td>56 分</td><td>AA Index</td></tr>\n        <tr><td>#3</td><td>GPT-5.5 (xhigh)</td><td>openai</td><td>55 分</td><td>AA Index</td></tr>\n        <tr><td>#4</td><td>Claude Opus 4.7 (max)</td><td>anthropic</td><td>54 分</td><td>AA Index</td></tr>\n        <tr><td>#5</td><td>GPT-5.5 (high)</td><td>openai</td><td>53 分</td><td>AA Index</td></tr>\n        <tr><td>#6</td><td>GLM-5.2 (max)</td><td>zhipu</td><td>51 分</td><td>AA Index</td></tr>\n        <tr><td>#7</td><td>Gemini 3.5 Flash</td><td>google</td><td>50 分</td><td>AA Index</td></tr>\n        <tr><td>#8</td><td>Claude Sonnet 4.6 (max)</td><td>anthropic</td><td>47 分</td><td>AA Index</td></tr>\n        <tr><td>#9</td><td>Gemini 3.1 Pro Preview</td><td>google</td><td>46 分</td><td>AA Index</td></tr>\n        <tr><td>#10</td><td>Qwen3.7 Max</td><td>alibaba</td><td>46 分</td><td>AA Index</td></tr></tbody>\n        </table>\n      </section>",
          "sanitized_css": ".artificial-analysis-index-card { border: 1px solid currentColor; padding: 16px; }\n      .artificial-analysis-index-card table { width: 100%; border-collapse: collapse; }\n      .artificial-analysis-index-card th, .artificial-analysis-index-card td { padding: 8px; border-top: 1px solid currentColor; text-align: left; }",
          "dom_hash": "sha256:2a6211eed7acea0dbf188caca37b12ac5937ac03c08119c42ccd2e94f897d66e",
          "css_hash": "sha256:ca6c14bf5033437bf403050f8a1267f835b68aab80f54905dfa8ecc653808bbf"
        },
        "history_entries": []
      },
      "tracking_component_snapshot": {
        "source": "Artificial Analysis",
        "component_kind": "artificial_analysis_index",
        "source_url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index",
        "collected_at": "2026-06-27T18:34:22.805Z",
        "selector_version": "artificial-analysis-index-v1",
        "raw_dom_hash": "sha256:caa7d33c2116c5495c0ff87bb3af671e33346e063be109cb1e5beccdf50e227a",
        "data_hash": "sha256:372b493783431b6c2783e719654b77b8c110f45b5224da48a86d5741d4add2b8",
        "tabs": [
          {
            "id": "score",
            "label": "Score",
            "view": "score_table",
            "fallback_reason": ""
          }
        ],
        "series": [
          {
            "id": "artificial-analysis-score",
            "tab_id": "score",
            "label": "Score",
            "chart": "score_table",
            "rows": [
              {
                "rank": 1,
                "model": "Claude Fable 5 (with fallback)",
                "provider": "anthropic",
                "value": 60,
                "value_label": "60 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 2,
                "model": "Claude Opus 4.8 (max)",
                "provider": "anthropic",
                "value": 56,
                "value_label": "56 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 3,
                "model": "GPT-5.5 (xhigh)",
                "provider": "openai",
                "value": 55,
                "value_label": "55 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 4,
                "model": "Claude Opus 4.7 (max)",
                "provider": "anthropic",
                "value": 54,
                "value_label": "54 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 5,
                "model": "GPT-5.5 (high)",
                "provider": "openai",
                "value": 53,
                "value_label": "53 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 6,
                "model": "GLM-5.2 (max)",
                "provider": "zhipu",
                "value": 51,
                "value_label": "51 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 7,
                "model": "Gemini 3.5 Flash",
                "provider": "google",
                "value": 50,
                "value_label": "50 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 8,
                "model": "Claude Sonnet 4.6 (max)",
                "provider": "anthropic",
                "value": 47,
                "value_label": "47 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 9,
                "model": "Gemini 3.1 Pro Preview",
                "provider": "google",
                "value": 46,
                "value_label": "46 分",
                "change": "AA Index",
                "metric": "Score"
              },
              {
                "rank": 10,
                "model": "Qwen3.7 Max",
                "provider": "alibaba",
                "value": 46,
                "value_label": "46 分",
                "change": "AA Index",
                "metric": "Score"
              }
            ],
            "fallback_reason": ""
          }
        ],
        "rows": [
          {
            "rank": 1,
            "model": "Claude Fable 5 (with fallback)",
            "provider": "anthropic",
            "value": 60,
            "value_label": "60 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 2,
            "model": "Claude Opus 4.8 (max)",
            "provider": "anthropic",
            "value": 56,
            "value_label": "56 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 3,
            "model": "GPT-5.5 (xhigh)",
            "provider": "openai",
            "value": 55,
            "value_label": "55 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 4,
            "model": "Claude Opus 4.7 (max)",
            "provider": "anthropic",
            "value": 54,
            "value_label": "54 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 5,
            "model": "GPT-5.5 (high)",
            "provider": "openai",
            "value": 53,
            "value_label": "53 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 6,
            "model": "GLM-5.2 (max)",
            "provider": "zhipu",
            "value": 51,
            "value_label": "51 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 7,
            "model": "Gemini 3.5 Flash",
            "provider": "google",
            "value": 50,
            "value_label": "50 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 8,
            "model": "Claude Sonnet 4.6 (max)",
            "provider": "anthropic",
            "value": 47,
            "value_label": "47 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 9,
            "model": "Gemini 3.1 Pro Preview",
            "provider": "google",
            "value": 46,
            "value_label": "46 分",
            "change": "AA Index",
            "metric": "AA Index"
          },
          {
            "rank": 10,
            "model": "Qwen3.7 Max",
            "provider": "alibaba",
            "value": 46,
            "value_label": "46 分",
            "change": "AA Index",
            "metric": "AA Index"
          }
        ],
        "previous_snapshot": null,
        "diff": {
          "summary": "No previous component snapshot was available for comparison.",
          "changed_rows": [],
          "new_entries": [
            "Claude Fable 5 (with fallback)",
            "Claude Opus 4.8 (max)",
            "GPT-5.5 (xhigh)",
            "Claude Opus 4.7 (max)",
            "GPT-5.5 (high)",
            "GLM-5.2 (max)",
            "Gemini 3.5 Flash",
            "Claude Sonnet 4.6 (max)",
            "Gemini 3.1 Pro Preview",
            "Qwen3.7 Max"
          ]
        },
        "cache_path": "",
        "fallback_reason": "",
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "artificial_analysis_index",
          "source_url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index",
          "captured_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "artificial-analysis-index-v1",
          "source_selector": "[data-artificial-analysis-index]",
          "sanitized_html": "<section class=\"artificial-analysis-index-card\" data-artificial-analysis-index>\n        <header>\n          <p>Artificial Analysis Intelligence Index</p>\n          <span>Top models by independent Intelligence Index</span>\n        </header>\n        <table>\n          <thead><tr><th>Rank</th><th>Model</th><th>Provider</th><th>Score</th><th>Metric</th></tr></thead>\n          <tbody>\n        <tr><td>#1</td><td>Claude Fable 5 (with fallback)</td><td>anthropic</td><td>60 分</td><td>AA Index</td></tr>\n        <tr><td>#2</td><td>Claude Opus 4.8 (max)</td><td>anthropic</td><td>56 分</td><td>AA Index</td></tr>\n        <tr><td>#3</td><td>GPT-5.5 (xhigh)</td><td>openai</td><td>55 分</td><td>AA Index</td></tr>\n        <tr><td>#4</td><td>Claude Opus 4.7 (max)</td><td>anthropic</td><td>54 分</td><td>AA Index</td></tr>\n        <tr><td>#5</td><td>GPT-5.5 (high)</td><td>openai</td><td>53 分</td><td>AA Index</td></tr>\n        <tr><td>#6</td><td>GLM-5.2 (max)</td><td>zhipu</td><td>51 分</td><td>AA Index</td></tr>\n        <tr><td>#7</td><td>Gemini 3.5 Flash</td><td>google</td><td>50 分</td><td>AA Index</td></tr>\n        <tr><td>#8</td><td>Claude Sonnet 4.6 (max)</td><td>anthropic</td><td>47 分</td><td>AA Index</td></tr>\n        <tr><td>#9</td><td>Gemini 3.1 Pro Preview</td><td>google</td><td>46 分</td><td>AA Index</td></tr>\n        <tr><td>#10</td><td>Qwen3.7 Max</td><td>alibaba</td><td>46 分</td><td>AA Index</td></tr></tbody>\n        </table>\n      </section>",
          "sanitized_css": ".artificial-analysis-index-card { border: 1px solid currentColor; padding: 16px; }\n      .artificial-analysis-index-card table { width: 100%; border-collapse: collapse; }\n      .artificial-analysis-index-card th, .artificial-analysis-index-card td { padding: 8px; border-top: 1px solid currentColor; text-align: left; }",
          "dom_hash": "sha256:2a6211eed7acea0dbf188caca37b12ac5937ac03c08119c42ccd2e94f897d66e",
          "css_hash": "sha256:ca6c14bf5033437bf403050f8a1267f835b68aab80f54905dfa8ecc653808bbf"
        },
        "public_trace": {
          "source_url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index",
          "collected_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "artificial-analysis-index-v1",
          "data_hash": "sha256:372b493783431b6c2783e719654b77b8c110f45b5224da48a86d5741d4add2b8",
          "top_rows": [
            {
              "rank": 1,
              "model": "Claude Fable 5 (with fallback)",
              "provider": "anthropic",
              "value_label": "60 分",
              "change": "AA Index"
            },
            {
              "rank": 2,
              "model": "Claude Opus 4.8 (max)",
              "provider": "anthropic",
              "value_label": "56 分",
              "change": "AA Index"
            },
            {
              "rank": 3,
              "model": "GPT-5.5 (xhigh)",
              "provider": "openai",
              "value_label": "55 分",
              "change": "AA Index"
            },
            {
              "rank": 4,
              "model": "Claude Opus 4.7 (max)",
              "provider": "anthropic",
              "value_label": "54 分",
              "change": "AA Index"
            },
            {
              "rank": 5,
              "model": "GPT-5.5 (high)",
              "provider": "openai",
              "value_label": "53 分",
              "change": "AA Index"
            },
            {
              "rank": 6,
              "model": "GLM-5.2 (max)",
              "provider": "zhipu",
              "value_label": "51 分",
              "change": "AA Index"
            },
            {
              "rank": 7,
              "model": "Gemini 3.5 Flash",
              "provider": "google",
              "value_label": "50 分",
              "change": "AA Index"
            },
            {
              "rank": 8,
              "model": "Claude Sonnet 4.6 (max)",
              "provider": "anthropic",
              "value_label": "47 分",
              "change": "AA Index"
            },
            {
              "rank": 9,
              "model": "Gemini 3.1 Pro Preview",
              "provider": "google",
              "value_label": "46 分",
              "change": "AA Index"
            },
            {
              "rank": 10,
              "model": "Qwen3.7 Max",
              "provider": "alibaba",
              "value_label": "46 分",
              "change": "AA Index"
            }
          ],
          "diff": {
            "summary": "No previous component snapshot was available for comparison.",
            "changed_rows": [],
            "new_entries": [
              "Claude Fable 5 (with fallback)",
              "Claude Opus 4.8 (max)",
              "GPT-5.5 (xhigh)",
              "Claude Opus 4.7 (max)",
              "GPT-5.5 (high)",
              "GLM-5.2 (max)",
              "Gemini 3.5 Flash",
              "Claude Sonnet 4.6 (max)",
              "Gemini 3.1 Pro Preview",
              "Qwen3.7 Max"
            ]
          },
          "cache_status": "live",
          "fallback_reason": ""
        }
      }
    },
    {
      "id": "swe-bench-pro-public",
      "name": "SWE-bench Pro",
      "url": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
      "event_date": "2026-06-28",
      "source": "Scale Labs SWE-Bench Pro",
      "category": "coding_benchmark",
      "importance": "major",
      "change_status": "changed",
      "change_summary": "SWE-bench Pro Public Dataset Top 10 已解析：#1 gpt-5.4 (xHigh)* 59.10±3.56%，#2 Muse Spark* 55.00±3.60%，#3 claude-opus-4-6 (thinking)* 51.90±3.61%；新进榜条目包括 Muse Spark*。",
      "summary": "Scale Labs 公开榜单显示，SWE-bench Pro Public Dataset 当前第一是 gpt-5.4 (xHigh)*（openai，Resolve Rate 59.10±3.56%）。 前三名为 gpt-5.4 (xHigh)* 59.10±3.56%、Muse Spark* 55.00±3.60%、claude-opus-4-6 (thinking)* 51.90±3.61%，Top 10 供应商分布为 anthropic 4、openai 3、google 2、scale 1。 这个榜单适合观察 coding agent 在长周期真实工程任务上的相对表现，但生产选型仍要结合 scaffold、成本上限、置信区间和团队自有仓库复测。",
      "watch_points": [
        "榜首 gpt-5.4 (xHigh)* 的 Resolve Rate 为 59.10±3.56%，需要看它是否依赖特定 agent scaffold 或成本上限。",
        "新进榜条目：Muse Spark*（scale）。",
        "把 SWE-bench Pro 与真实 IDE/CI 工作流分开看，避免把公开 benchmark 直接等同于团队仓库里的修复率。"
      ],
      "metrics": [
        {
          "label": "榜单范围",
          "value": "SWE-bench Pro Public Top 10",
          "trend": "same"
        },
        {
          "label": "供应商分布",
          "value": "anthropic 4、openai 3、google 2、scale 1",
          "trend": "unknown"
        },
        {
          "label": "#1",
          "value": "gpt-5.4 (xHigh)*（openai）：Resolve Rate 59.10±3.56%",
          "trend": "unknown"
        },
        {
          "label": "#2",
          "value": "Muse Spark*（scale）：Resolve Rate 55.00±3.60%",
          "trend": "new"
        },
        {
          "label": "#3",
          "value": "claude-opus-4-6 (thinking)*（anthropic）：Resolve Rate 51.90±3.61%",
          "trend": "unknown"
        },
        {
          "label": "#4",
          "value": "gemini-3.1-pro (thinking)*（google）：Resolve Rate 46.10±3.60%",
          "trend": "unknown"
        },
        {
          "label": "#5",
          "value": "claude-opus-4-5-20251101（anthropic）：Resolve Rate 45.89±3.60%",
          "trend": "unknown"
        },
        {
          "label": "#6",
          "value": "claude-4-5-Sonnet（anthropic）：Resolve Rate 43.60±3.60%",
          "trend": "unknown"
        },
        {
          "label": "#7",
          "value": "gemini-3-pro-preview（google）：Resolve Rate 43.30±3.60%",
          "trend": "unknown"
        },
        {
          "label": "#8",
          "value": "claude-4-Sonnet（anthropic）：Resolve Rate 42.70±3.59%",
          "trend": "unknown"
        },
        {
          "label": "#9",
          "value": "gpt-5-2025-08-07 (High)（openai）：Resolve Rate 41.78±3.49%",
          "trend": "unknown"
        },
        {
          "label": "#10",
          "value": "gpt-5.2-codex（openai）：Resolve Rate 41.04±3.57%",
          "trend": "unknown"
        }
      ],
      "snapshot": {
        "type": "swe_bench_pro_public_page",
        "collection_method": "public_page_static",
        "snapshot_status": "complete",
        "snapshot_as_of": "2026-06-27T18:34:22.805Z",
        "source_url": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
        "top_entries": [
          {
            "rank": 1,
            "model": "gpt-5.4 (xHigh)*",
            "provider": "openai",
            "tokens": "59.10±3.56%",
            "change": "Resolve Rate"
          },
          {
            "rank": 2,
            "model": "Muse Spark*",
            "provider": "scale",
            "tokens": "55.00±3.60%",
            "change": "new"
          },
          {
            "rank": 3,
            "model": "claude-opus-4-6 (thinking)*",
            "provider": "anthropic",
            "tokens": "51.90±3.61%",
            "change": "Resolve Rate"
          },
          {
            "rank": 4,
            "model": "gemini-3.1-pro (thinking)*",
            "provider": "google",
            "tokens": "46.10±3.60%",
            "change": "Resolve Rate"
          },
          {
            "rank": 5,
            "model": "claude-opus-4-5-20251101",
            "provider": "anthropic",
            "tokens": "45.89±3.60%",
            "change": "Resolve Rate"
          },
          {
            "rank": 6,
            "model": "claude-4-5-Sonnet",
            "provider": "anthropic",
            "tokens": "43.60±3.60%",
            "change": "Resolve Rate"
          },
          {
            "rank": 7,
            "model": "gemini-3-pro-preview",
            "provider": "google",
            "tokens": "43.30±3.60%",
            "change": "Resolve Rate"
          },
          {
            "rank": 8,
            "model": "claude-4-Sonnet",
            "provider": "anthropic",
            "tokens": "42.70±3.59%",
            "change": "Resolve Rate"
          },
          {
            "rank": 9,
            "model": "gpt-5-2025-08-07 (High)",
            "provider": "openai",
            "tokens": "41.78±3.49%",
            "change": "Resolve Rate"
          },
          {
            "rank": 10,
            "model": "gpt-5.2-codex",
            "provider": "openai",
            "tokens": "41.04±3.57%",
            "change": "Resolve Rate"
          }
        ],
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "swe_bench_pro",
          "source_url": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
          "captured_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "swe-bench-pro-v1",
          "source_selector": "[data-swe-bench-pro-leaderboard]",
          "sanitized_html": "<section class=\"swe-bench-pro-card\" data-swe-bench-pro-leaderboard>\n        <header>\n          <p>SWE-Bench Pro (Public Dataset)</p>\n          <h2>Performance Comparison</h2>\n          <span>Primary metric: Resolve Rate</span>\n        </header>\n        <table>\n          <thead><tr><th>Rank</th><th>Model / Agent</th><th>Provider</th><th>Resolve Rate</th><th>Change</th></tr></thead>\n          <tbody>\n        <tr>\n          <td>#1</td>\n          <td>gpt-5.4 (xHigh)*</td>\n          <td>openai</td>\n          <td>59.10±3.56%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#2</td>\n          <td>Muse Spark*</td>\n          <td>scale</td>\n          <td>55.00±3.60%</td>\n          <td>new</td>\n        </tr>\n        <tr>\n          <td>#3</td>\n          <td>claude-opus-4-6 (thinking)*</td>\n          <td>anthropic</td>\n          <td>51.90±3.61%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#4</td>\n          <td>gemini-3.1-pro (thinking)*</td>\n          <td>google</td>\n          <td>46.10±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#5</td>\n          <td>claude-opus-4-5-20251101</td>\n          <td>anthropic</td>\n          <td>45.89±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#6</td>\n          <td>claude-4-5-Sonnet</td>\n          <td>anthropic</td>\n          <td>43.60±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#7</td>\n          <td>gemini-3-pro-preview</td>\n          <td>google</td>\n          <td>43.30±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#8</td>\n          <td>claude-4-Sonnet</td>\n          <td>anthropic</td>\n          <td>42.70±3.59%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#9</td>\n          <td>gpt-5-2025-08-07 (High)</td>\n          <td>openai</td>\n          <td>41.78±3.49%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#10</td>\n          <td>gpt-5.2-codex</td>\n          <td>openai</td>\n          <td>41.04±3.57%</td>\n          <td>Resolve Rate</td>\n        </tr></tbody>\n        </table>\n      </section>",
          "sanitized_css": ".swe-bench-pro-card { border: 1px solid currentColor; padding: 16px; }\n      .swe-bench-pro-card table { width: 100%; border-collapse: collapse; }\n      .swe-bench-pro-card th, .swe-bench-pro-card td { padding: 8px; border-top: 1px solid currentColor; text-align: left; }",
          "dom_hash": "sha256:cc4506cfb6f43dc3ea7331ad2e9ab545ed056a3aab2309bf4201d14baa1ce040",
          "css_hash": "sha256:bbb18aff9c5bd0f35808108d31a64c2b62e0adcab81b24181da21bcd9a31c42d"
        },
        "history_entries": []
      },
      "tracking_component_snapshot": {
        "source": "Scale Labs SWE-Bench Pro",
        "component_kind": "swe_bench_pro",
        "source_url": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
        "collected_at": "2026-06-27T18:34:22.805Z",
        "selector_version": "swe-bench-pro-v1",
        "raw_dom_hash": "sha256:2d5ebf88219cf9ca3b8537c2a99a9339988bd6f4b8cb73e80b37c9c1e786a9a9",
        "data_hash": "sha256:c8b9855ed707267e22d55555df028b72d17fc37bb120aacc96de86e8da417fa7",
        "tabs": [
          {
            "id": "leaderboard",
            "label": "Public Leaderboard",
            "view": "leaderboard",
            "fallback_reason": ""
          }
        ],
        "series": [
          {
            "id": "swe-bench-pro-public-leaderboard",
            "tab_id": "leaderboard",
            "label": "SWE-Bench Pro Public Dataset",
            "chart": "leaderboard",
            "rows": [
              {
                "rank": 1,
                "model": "gpt-5.4 (xHigh)*",
                "provider": "openai",
                "value": 59.1,
                "value_label": "59.10±3.56%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 2,
                "model": "Muse Spark*",
                "provider": "scale",
                "value": 55,
                "value_label": "55.00±3.60%",
                "change": "new",
                "metric": "Resolve Rate"
              },
              {
                "rank": 3,
                "model": "claude-opus-4-6 (thinking)*",
                "provider": "anthropic",
                "value": 51.9,
                "value_label": "51.90±3.61%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 4,
                "model": "gemini-3.1-pro (thinking)*",
                "provider": "google",
                "value": 46.1,
                "value_label": "46.10±3.60%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 5,
                "model": "claude-opus-4-5-20251101",
                "provider": "anthropic",
                "value": 45.89,
                "value_label": "45.89±3.60%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 6,
                "model": "claude-4-5-Sonnet",
                "provider": "anthropic",
                "value": 43.6,
                "value_label": "43.60±3.60%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 7,
                "model": "gemini-3-pro-preview",
                "provider": "google",
                "value": 43.3,
                "value_label": "43.30±3.60%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 8,
                "model": "claude-4-Sonnet",
                "provider": "anthropic",
                "value": 42.7,
                "value_label": "42.70±3.59%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 9,
                "model": "gpt-5-2025-08-07 (High)",
                "provider": "openai",
                "value": 41.78,
                "value_label": "41.78±3.49%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              },
              {
                "rank": 10,
                "model": "gpt-5.2-codex",
                "provider": "openai",
                "value": 41.04,
                "value_label": "41.04±3.57%",
                "change": "Resolve Rate",
                "metric": "Resolve Rate"
              }
            ],
            "fallback_reason": ""
          }
        ],
        "rows": [
          {
            "rank": 1,
            "model": "gpt-5.4 (xHigh)*",
            "provider": "openai",
            "value": 59.1,
            "value_label": "59.10±3.56%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 2,
            "model": "Muse Spark*",
            "provider": "scale",
            "value": 55,
            "value_label": "55.00±3.60%",
            "change": "new",
            "metric": "Resolve Rate"
          },
          {
            "rank": 3,
            "model": "claude-opus-4-6 (thinking)*",
            "provider": "anthropic",
            "value": 51.9,
            "value_label": "51.90±3.61%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 4,
            "model": "gemini-3.1-pro (thinking)*",
            "provider": "google",
            "value": 46.1,
            "value_label": "46.10±3.60%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 5,
            "model": "claude-opus-4-5-20251101",
            "provider": "anthropic",
            "value": 45.89,
            "value_label": "45.89±3.60%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 6,
            "model": "claude-4-5-Sonnet",
            "provider": "anthropic",
            "value": 43.6,
            "value_label": "43.60±3.60%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 7,
            "model": "gemini-3-pro-preview",
            "provider": "google",
            "value": 43.3,
            "value_label": "43.30±3.60%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 8,
            "model": "claude-4-Sonnet",
            "provider": "anthropic",
            "value": 42.7,
            "value_label": "42.70±3.59%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 9,
            "model": "gpt-5-2025-08-07 (High)",
            "provider": "openai",
            "value": 41.78,
            "value_label": "41.78±3.49%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          },
          {
            "rank": 10,
            "model": "gpt-5.2-codex",
            "provider": "openai",
            "value": 41.04,
            "value_label": "41.04±3.57%",
            "change": "Resolve Rate",
            "metric": "Resolve Rate"
          }
        ],
        "previous_snapshot": null,
        "diff": {
          "summary": "No previous component snapshot was available for comparison.",
          "changed_rows": [],
          "new_entries": [
            "gpt-5.4 (xHigh)*",
            "Muse Spark*",
            "claude-opus-4-6 (thinking)*",
            "gemini-3.1-pro (thinking)*",
            "claude-opus-4-5-20251101",
            "claude-4-5-Sonnet",
            "gemini-3-pro-preview",
            "claude-4-Sonnet",
            "gpt-5-2025-08-07 (High)",
            "gpt-5.2-codex"
          ]
        },
        "cache_path": "",
        "fallback_reason": "",
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "swe_bench_pro",
          "source_url": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
          "captured_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "swe-bench-pro-v1",
          "source_selector": "[data-swe-bench-pro-leaderboard]",
          "sanitized_html": "<section class=\"swe-bench-pro-card\" data-swe-bench-pro-leaderboard>\n        <header>\n          <p>SWE-Bench Pro (Public Dataset)</p>\n          <h2>Performance Comparison</h2>\n          <span>Primary metric: Resolve Rate</span>\n        </header>\n        <table>\n          <thead><tr><th>Rank</th><th>Model / Agent</th><th>Provider</th><th>Resolve Rate</th><th>Change</th></tr></thead>\n          <tbody>\n        <tr>\n          <td>#1</td>\n          <td>gpt-5.4 (xHigh)*</td>\n          <td>openai</td>\n          <td>59.10±3.56%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#2</td>\n          <td>Muse Spark*</td>\n          <td>scale</td>\n          <td>55.00±3.60%</td>\n          <td>new</td>\n        </tr>\n        <tr>\n          <td>#3</td>\n          <td>claude-opus-4-6 (thinking)*</td>\n          <td>anthropic</td>\n          <td>51.90±3.61%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#4</td>\n          <td>gemini-3.1-pro (thinking)*</td>\n          <td>google</td>\n          <td>46.10±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#5</td>\n          <td>claude-opus-4-5-20251101</td>\n          <td>anthropic</td>\n          <td>45.89±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#6</td>\n          <td>claude-4-5-Sonnet</td>\n          <td>anthropic</td>\n          <td>43.60±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#7</td>\n          <td>gemini-3-pro-preview</td>\n          <td>google</td>\n          <td>43.30±3.60%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#8</td>\n          <td>claude-4-Sonnet</td>\n          <td>anthropic</td>\n          <td>42.70±3.59%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#9</td>\n          <td>gpt-5-2025-08-07 (High)</td>\n          <td>openai</td>\n          <td>41.78±3.49%</td>\n          <td>Resolve Rate</td>\n        </tr>\n        <tr>\n          <td>#10</td>\n          <td>gpt-5.2-codex</td>\n          <td>openai</td>\n          <td>41.04±3.57%</td>\n          <td>Resolve Rate</td>\n        </tr></tbody>\n        </table>\n      </section>",
          "sanitized_css": ".swe-bench-pro-card { border: 1px solid currentColor; padding: 16px; }\n      .swe-bench-pro-card table { width: 100%; border-collapse: collapse; }\n      .swe-bench-pro-card th, .swe-bench-pro-card td { padding: 8px; border-top: 1px solid currentColor; text-align: left; }",
          "dom_hash": "sha256:cc4506cfb6f43dc3ea7331ad2e9ab545ed056a3aab2309bf4201d14baa1ce040",
          "css_hash": "sha256:bbb18aff9c5bd0f35808108d31a64c2b62e0adcab81b24181da21bcd9a31c42d"
        },
        "public_trace": {
          "source_url": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
          "collected_at": "2026-06-27T18:34:22.805Z",
          "selector_version": "swe-bench-pro-v1",
          "data_hash": "sha256:c8b9855ed707267e22d55555df028b72d17fc37bb120aacc96de86e8da417fa7",
          "top_rows": [
            {
              "rank": 1,
              "model": "gpt-5.4 (xHigh)*",
              "provider": "openai",
              "value_label": "59.10±3.56%",
              "change": "Resolve Rate"
            },
            {
              "rank": 2,
              "model": "Muse Spark*",
              "provider": "scale",
              "value_label": "55.00±3.60%",
              "change": "new"
            },
            {
              "rank": 3,
              "model": "claude-opus-4-6 (thinking)*",
              "provider": "anthropic",
              "value_label": "51.90±3.61%",
              "change": "Resolve Rate"
            },
            {
              "rank": 4,
              "model": "gemini-3.1-pro (thinking)*",
              "provider": "google",
              "value_label": "46.10±3.60%",
              "change": "Resolve Rate"
            },
            {
              "rank": 5,
              "model": "claude-opus-4-5-20251101",
              "provider": "anthropic",
              "value_label": "45.89±3.60%",
              "change": "Resolve Rate"
            },
            {
              "rank": 6,
              "model": "claude-4-5-Sonnet",
              "provider": "anthropic",
              "value_label": "43.60±3.60%",
              "change": "Resolve Rate"
            },
            {
              "rank": 7,
              "model": "gemini-3-pro-preview",
              "provider": "google",
              "value_label": "43.30±3.60%",
              "change": "Resolve Rate"
            },
            {
              "rank": 8,
              "model": "claude-4-Sonnet",
              "provider": "anthropic",
              "value_label": "42.70±3.59%",
              "change": "Resolve Rate"
            },
            {
              "rank": 9,
              "model": "gpt-5-2025-08-07 (High)",
              "provider": "openai",
              "value_label": "41.78±3.49%",
              "change": "Resolve Rate"
            },
            {
              "rank": 10,
              "model": "gpt-5.2-codex",
              "provider": "openai",
              "value_label": "41.04±3.57%",
              "change": "Resolve Rate"
            }
          ],
          "diff": {
            "summary": "No previous component snapshot was available for comparison.",
            "changed_rows": [],
            "new_entries": [
              "gpt-5.4 (xHigh)*",
              "Muse Spark*",
              "claude-opus-4-6 (thinking)*",
              "gemini-3.1-pro (thinking)*",
              "claude-opus-4-5-20251101",
              "claude-4-5-Sonnet",
              "gemini-3-pro-preview",
              "claude-4-Sonnet",
              "gpt-5-2025-08-07 (High)",
              "gpt-5.2-codex"
            ]
          },
          "cache_status": "live",
          "fallback_reason": ""
        }
      }
    }
  ],
  "projects": [
    {
      "name": "calesthio/OpenMontage",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/calesthio/OpenMontage",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "DeusData/codebase-memory-mcp",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/DeusData/codebase-memory-mcp",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "kunchenguid/no-mistakes",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/kunchenguid/no-mistakes",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "google-labs-code/design.md",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/google-labs-code/design.md",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "ZhuLinsen/daily_stock_analysis",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/ZhuLinsen/daily_stock_analysis",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "penpot/penpot",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/penpot/penpot",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "Panniantong/Agent-Reach",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/Panniantong/Agent-Reach",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "interviewstreet/hiring-agent",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/interviewstreet/hiring-agent",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "JCodesMore/ai-website-cloner-template",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/JCodesMore/ai-website-cloner-template",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "jamiepine/voicebox",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/jamiepine/voicebox",
      "event_date": "2026-06-28",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    }
  ],
  "builder_observations": [
    {
      "author": "Swyx",
      "handle": "swyx",
      "editorial_category": "x_discussion",
      "content": "swyx说，自己一直与契合领域专家合作扩展覆盖范围，以避免低质扩张；随着 OpenAI 和 Anthropic 都推出数十亿美元级服务部门，他认为 FDE 已成为最受需求的岗位之一，并提到下周将与 Basil 举办首场 AI FDE 小型会议。",
      "original_text": "we have been scaling without slop by working with aligned domain experts to add coverage with both oai and ant launching multi-billion dollar services arms, it’s clear that FDE is one of the most in demand disciplines on earth, but I have never done the job it’s been an absolute pleasure working with Basil on our first ever AI FDE miniconference! see at https://t.co/STlx7OsWbr next week",
      "translation": "swyx说，自己一直与契合领域专家合作扩展覆盖范围，以避免低质扩张；随着 OpenAI 和 Anthropic 都推出数十亿美元级服务部门，他认为 FDE 已成为最受需求的岗位之一，并提到下周将与 Basil 举办首场 AI FDE 小型会议。",
      "avatar_url": "https://unavatar.io/x/swyx",
      "url": "https://x.com/swyx/status/2070606851377672675",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Guillermo Rauch",
      "handle": "rauchg",
      "editorial_category": "x_discussion",
      "content": "Guillermo Rauch 指出，agent 尤其难调试：模型本身非确定，同样的提示不一定产生同样输出；agent 又像复杂分布式系统，会跨函数、沙箱和大量 API 服务多步运行，因此 Vercel 为 v0 做开箱可观测性是团队重点。",
      "original_text": "Agents are particularly hard-to-debug software. For one, and by design, AI models behave in non-deterministic ways. Even two identical prompts don't always yield the same output. But agents are also complex distributed systems. They involve multiple steps of computation across functions and sandboxes, touching dozens of API services that can go down, rate limit you, etc. Nailing down observability out of the box for https://t.co/nDDXqUmOlD on Vercel was a key priority for the team, and the feed...",
      "translation": "Guillermo Rauch 指出，agent 尤其难调试：模型本身非确定，同样的提示不一定产生同样输出；agent 又像复杂分布式系统，会跨函数、沙箱和大量 API 服务多步运行，因此 Vercel 为 v0 做开箱可观测性是团队重点。",
      "avatar_url": "https://unavatar.io/x/rauchg",
      "url": "https://x.com/rauchg/status/2070676383135834334",
      "role": "builder",
      "event_date": "2026-06-27",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Garry Tan",
      "handle": "garrytan",
      "editorial_category": "x_discussion",
      "content": "Garry Tan 批评某个模型的发布方式不合理，认为如果继续这样开发和发布，会破坏小型创业公司的创新空间。",
      "original_text": "This is honestly no way to release a model and continued development and release this way is a solid way to salt the ground and kill all innovation by small startups https://t.co/tUjxFSunVI",
      "translation": "Garry Tan 批评某个模型的发布方式不合理，认为如果继续这样开发和发布，会破坏小型创业公司的创新空间。",
      "avatar_url": "https://unavatar.io/x/garrytan",
      "url": "https://x.com/garrytan/status/2070699046939820223",
      "role": "builder",
      "event_date": "2026-06-27",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Thibault Sottiaux",
      "handle": "thsottiaux",
      "editorial_category": "x_discussion",
      "content": "Thibault Sottiaux 说，所有 Codex 用户都会获得一次使用量重置，接下来几小时会显示在账户中；团队已采取一些缓解措施，调查尚未显示用户受到大范围影响，并会继续监控。",
      "original_text": "We are giving all Codex users a usage reset on the house. Should be showing in your accounts in the next few hours. We have applied some mitigations, but our investigation hasn't shown users being impacted at large. We are continuing to monitor the situation. https://t.co/rLJrQdI1ks",
      "translation": "Thibault Sottiaux 说，所有 Codex 用户都会获得一次使用量重置，接下来几小时会显示在账户中；团队已采取一些缓解措施，调查尚未显示用户受到大范围影响，并会继续监控。",
      "avatar_url": "https://unavatar.io/x/thsottiaux",
      "url": "https://x.com/thsottiaux/status/2070653282440405046",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Peter Yang",
      "handle": "petergyang",
      "editorial_category": "x_discussion",
      "content": "Peter Yang 观察到，资金更多流向服务以及捆绑部分软件，而不是纯软件；客户想要结果而不是工具，因此他觉得只做纯软件公司很难比使用 Codex 或 Claude Code 加上一组个人技能和 agent 更有价值，并征求看法。",
      "original_text": "From what I'm seeing, alot of the money has moved to services (with some software bundled), not software. People want outcomes, not tools. It's feels really hard to build a pure-play software company that's more valuable to people or companies than just using Codex/Claude Code with a bunch of personal skills and agents. Thoughts?",
      "translation": "Peter Yang 观察到，资金更多流向服务以及捆绑部分软件，而不是纯软件；客户想要结果而不是工具，因此他觉得只做纯软件公司很难比使用 Codex 或 Claude Code 加上一组个人技能和 agent 更有价值，并征求看法。",
      "avatar_url": "https://unavatar.io/x/petergyang",
      "url": "https://x.com/petergyang/status/2070568705365577990",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Peter Yang",
      "handle": "petergyang",
      "editorial_category": "x_discussion",
      "content": "Peter Yang 列出希望 Claude Code 改进的小功能：恢复在 Claude 工作时继续引导对话的能力，默认开启所有线程的移动端远程控制，支持类似 cmd 加按键的线程快捷键并在按住 cmd 时显示提示，以及允许拖拽重排左侧项目。",
      "original_text": "Small things I wish Claude Code had: 1. Bring back ability to steer conversations while Claude is working 2. Make mobile remote control for all threads on by default 3. The shortcut keys seem only accessible if you have the sub-menu open? Consider supporting \"cmd + key\" so we can hotkey to different threads with the keyboard. If I hold down cmd I should see all the shortcuts in the UI. 4. Let me drag and drop to re-arrange my projects on left nav",
      "translation": "Peter Yang 列出希望 Claude Code 改进的小功能：恢复在 Claude 工作时继续引导对话的能力，默认开启所有线程的移动端远程控制，支持类似 cmd 加按键的线程快捷键并在按住 cmd 时显示提示，以及允许拖拽重排左侧项目。",
      "avatar_url": "https://unavatar.io/x/petergyang",
      "url": "https://x.com/petergyang/status/2070545325497221248",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Cat Wu",
      "handle": "_catwu",
      "editorial_category": "x_discussion",
      "content": "Cat Wu 说，桌面端 Claude Code 的分屏是她最喜欢的功能之一。",
      "original_text": "split screen is one of my fave claude code on desktop features! https://t.co/4ZQZjBnmvL",
      "translation": "Cat Wu 说，桌面端 Claude Code 的分屏是她最喜欢的功能之一。",
      "avatar_url": "https://unavatar.io/x/_catwu",
      "url": "https://x.com/_catwu/status/2070613405237432766",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Guillermo Rauch",
      "handle": "rauchg",
      "editorial_category": "x_discussion",
      "content": "Guillermo Rauch 说，面向 AI 的 UI 已经出现，他指向 shadcn。",
      "original_text": "The UI for AI is here. It's @shadcn https://t.co/bzgEEKO9Az",
      "translation": "Guillermo Rauch 说，面向 AI 的 UI 已经出现，他指向 shadcn。",
      "avatar_url": "https://unavatar.io/x/rauchg",
      "url": "https://x.com/rauchg/status/2070567538040422712",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Aaron Levie",
      "handle": "levie",
      "editorial_category": "x_discussion",
      "content": "Aaron Levie 认为 GPT-5.6 真实存在且表现很强，尤其适合需要大量工具使用和长时间 agent 执行的知识工作任务；他同时表示当前 AI 进展还没有撞墙。",
      "original_text": "GPT-5.6 is real and looks very strong. Going to be very strong for knowledge worker tasks that require heavy tool use and long running agents doing work. We're not hitting any walls in AI progress right now. https://t.co/5Apn3VzmkY https://t.co/LGpfF8ANcT",
      "translation": "Aaron Levie 认为 GPT-5.6 真实存在且表现很强，尤其适合需要大量工具使用和长时间 agent 执行的知识工作任务；他同时表示当前 AI 进展还没有撞墙。",
      "avatar_url": "https://unavatar.io/x/levie",
      "url": "https://x.com/levie/status/2070563281916620895",
      "role": "builder",
      "event_date": "2026-06-26",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    }
  ],
  "official_org_updates": [],
  "evidence_assets": [],
  "generated_at": "2026-06-27T18:39:52.096Z",
  "report_status": "normal",
  "canonical_url": "https://jasonxzwen.github.io/ai-daily-cn/reports/2026/06/2026-06-28.html",
  "html_path": "reports/2026/06/2026-06-28.html",
  "quality_status": {
    "status": "degraded",
    "public_note": "Some discovery coverage is degraded; this report may be incomplete.",
    "degraded_events": [
      {
        "section": "hot_blogs",
        "message": "China AI source lane ran successfully but produced no recent candidates.",
        "severity": "degraded"
      }
    ]
  }
}