{
  "schema_version": 1,
  "report_date": "2026-06-24",
  "title": "AI 日报 2026-06-24",
  "summary": "今天最值得看的主线有 Alibaba Cloud披露 AIGC 创作工作流；Meta Newsroom更新AI 产品、平台或工程实践；Alibaba Cloud发布 Claude Code agent 工具工作流；热门博客这轮主要看 agent 和开发工具的落地边界。",
  "hero_highlights": [
    {
      "title": "OpenAI披露模型评估和研究结果",
      "url": "https://openai.com/index/gpt-5-immunology-mystery",
      "reason": "研究价值集中在评测设置、能力边界和内部实验参照",
      "what_happened": "OpenAI披露模型能力和评估方法更新，材料覆盖能力边界、评估设置、数据来源、使用场景和限制说明，边界落在结论仍要依赖可复现评测、真实任务和公开限制",
      "why_watch": "研究价值集中在评测设置、能力边界和内部实验参照",
      "category": "model_platform",
      "source_item_ref": "https://openai.com/index/gpt-5-immunology-mystery"
    },
    {
      "title": "Meta Newsroom更新AI 产品、平台或工程实践",
      "url": "https://about.fb.com/news/2026/06/meta-essilorluxottica-partner-launch-meta-glasses/",
      "reason": "信号集中在产品入口、采购时机和路线图影响",
      "what_happened": "Meta Newsroom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": "信号集中在产品入口、采购时机和路线图影响",
      "category": "product_tool",
      "source_item_ref": "https://about.fb.com/news/2026/06/meta-essilorluxottica-partner-launch-meta-glasses/"
    },
    {
      "title": "Alibaba Cloud披露 AIGC 创作工作流",
      "url": "https://www.alibabacloud.com/blog/happyhorse-gets-stronger-motion-expressiveness-higher-generation-consistency-and-enhanced-visual-quality_603293",
      "reason": "内容侧价值集中在素材生成、创作者工具链成本和交付方式",
      "what_happened": "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",
      "why_watch": "内容侧价值集中在素材生成、创作者工具链成本和交付方式",
      "category": "china_open_source_community",
      "source_item_ref": "https://www.alibabacloud.com/blog/happyhorse-gets-stronger-motion-expressiveness-higher-generation-consistency-and-enhanced-visual-quality_603293"
    }
  ],
  "stories": [
    {
      "story_id": "story-content-alibaba-cloud-blog-happyhorse-gets-stronger-motion-expressiveness-higher",
      "title": "Alibaba Cloud发布 AIGC 创作工作流",
      "importance": "general",
      "trend": "AI content workflow",
      "event_date": "2026-06-23",
      "primary_entity": "Alibaba Cloud Blog",
      "event_type": "update",
      "object": "Alibaba Cloud披露 AIGC 创作工作流",
      "what_happened": "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。",
      "why_it_matters": "内容侧价值集中在素材生成、创作者工具链成本和交付方式",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Alibaba Cloud Blog",
          "url": "https://www.alibabacloud.com/blog/happyhorse-gets-stronger-motion-expressiveness-higher-generation-consistency-and-enhanced-visual-quality_603293",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-meta-newsroom-we-re-partnering-with-essilorluxottica-to-launch-meta-glas",
      "title": "Meta Newsroom: Meta Essilorluxottica Partner Launch Meta Glasses",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-23",
      "primary_entity": "Meta Newsroom",
      "event_type": "launch",
      "object": "Meta Newsroom更新AI 产品、平台或工程实践",
      "what_happened": "Meta Newsroom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_it_matters": "信号集中在产品入口、采购时机和路线图影响",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Meta Newsroom",
          "url": "https://about.fb.com/news/2026/06/meta-essilorluxottica-partner-launch-meta-glasses/",
          "type": "primary"
        }
      ]
    },
    {
      "story_id": "story-content-alibaba-cloud-blog-alibaba-cloud-releases-anolisa-agentic-os-the-first-a",
      "title": "Alibaba Cloud发布 Claude Code agent 工具工作流",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-24",
      "primary_entity": "Alibaba Cloud Blog",
      "event_type": "signal",
      "object": "Alibaba Cloud发布 Claude Code agent 工具工作流",
      "what_happened": "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。",
      "why_it_matters": "工程侧价值集中在 agent、开发工具和自动化工作流接入",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Alibaba Cloud Blog",
          "url": "https://www.alibabacloud.com/blog/alibaba-cloud-releases-anolisa-agentic-os-the-first-agent-oriented-operating-system_603295",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-openai-news-how-gpt-5-helped-immunologist-derya-unutmaz-solve-a-3-year-o",
      "title": "OpenAI公布模型评估和研究结果",
      "importance": "general",
      "trend": "AI industry",
      "event_date": "2026-06-23",
      "primary_entity": "OpenAI News RSS",
      "event_type": "update",
      "object": "OpenAI披露模型评估和研究结果",
      "what_happened": "OpenAI披露模型能力和评估方法更新，材料覆盖能力边界、评估设置、数据来源、使用场景和限制说明，边界落在结论仍要依赖可复现评测、真实任务和公开限制。",
      "why_it_matters": "研究价值集中在评测设置、能力边界和内部实验参照",
      "evidence_level": "multi_source",
      "sources": [
        {
          "label": "OpenAI News RSS",
          "url": "https://openai.com/index/gpt-5-immunology-mystery",
          "type": "official"
        },
        {
          "label": "OpenAI Blog RSS",
          "url": "https://openai.com/index/gpt-5-immunology-mystery",
          "type": "official"
        },
        {
          "label": "OpenAI Company News RSS",
          "url": "https://openai.com/index/gpt-5-immunology-mystery",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-alibaba-cloud-blog-cross-platform-quant-trading-bringing-smart-q-into-ma",
      "title": "Alibaba Cloud更新agent 与开发者工具能力",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-23",
      "primary_entity": "Alibaba Cloud Blog",
      "event_type": "signal",
      "object": "Alibaba Cloud披露 agent 与开发者工具能力",
      "what_happened": "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。",
      "why_it_matters": "工程侧价值集中在 agent、开发工具和自动化工作流接入",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Alibaba Cloud Blog",
          "url": "https://www.alibabacloud.com/blog/cross-platform-quant-trading-bringing-smart-q-into-market-monitoring-and-trading-review_603291",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-openai-news-helping-build-shared-standards-for-advanced-ai",
      "title": "OpenAI说明安全治理和平台控制变化",
      "importance": "general",
      "trend": "AI industry",
      "event_date": "2026-06-23",
      "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披露模型能力和评估方法更新，材料覆盖能力边界、评估设置、数据来源、使用场景和限制说明，边界落在结论仍要依赖可复现评测、真实任务和公开限制。",
      "why_it_matters": "研究价值集中在评测设置、能力边界和内部实验参照",
      "evidence_level": "multi_source",
      "sources": [
        {
          "label": "OpenAI News RSS",
          "url": "https://openai.com/index/helping-build-shared-standards-for-advanced-ai",
          "type": "official"
        },
        {
          "label": "OpenAI Blog RSS",
          "url": "https://openai.com/index/helping-build-shared-standards-for-advanced-ai",
          "type": "official"
        },
        {
          "label": "OpenAI Company News RSS",
          "url": "https://openai.com/index/helping-build-shared-standards-for-advanced-ai",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-google-keyword-preserving-cultural-heritage-inside-google-deepmind-s-col",
      "title": "Google发布 AIGC 创作工作流",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-23",
      "primary_entity": "Google Keyword Blog",
      "event_type": "signal",
      "object": "Google披露 AIGC 创作工作流",
      "what_happened": "DeepMind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_it_matters": "信号集中在 AI 产品、模型或平台策略的实际变化",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Google Keyword Blog",
          "url": "https://blog.google/company-news/inside-google/around-the-globe/google-europe/preserving-cultural-heritage-inside-google-deepminds-collaboration-with-pele/",
          "type": "official"
        }
      ]
    },
    {
      "story_id": "story-content-microsoft-official-blog-rethinking-cloud-operations-with-agentic-observa",
      "title": "Microsoft更新agent 可观测平台更新",
      "importance": "general",
      "trend": "AI products and developer workflow",
      "event_date": "2026-06-23",
      "primary_entity": "Official Microsoft Blog",
      "event_type": "signal",
      "object": "Microsoft披露 agent 可观测平台更新",
      "what_happened": "微软研究院发布生产 agent 观测面板，材料覆盖工具调用轨迹、事故时间线、成本归因、回滚状态和发布健康度，边界落在观测价值取决于能否把失败记录、成本和发布状态串进同一条链路。",
      "why_it_matters": "工程侧价值集中在 agent、开发工具和自动化工作流接入",
      "evidence_level": "primary",
      "sources": [
        {
          "label": "Official Microsoft Blog",
          "url": "https://blogs.microsoft.com/blog/2026/06/23/rethinking-cloud-operations-with-agentic-observability/",
          "type": "official"
        }
      ]
    }
  ],
  "main_items": [
    {
      "title": "Alibaba Cloud发布 AIGC 创作工作流",
      "editorial_category": "content_aigc",
      "event_date": "2026-06-23",
      "url": "https://www.alibabacloud.com/blog/happyhorse-gets-stronger-motion-expressiveness-higher-generation-consistency-and-enhanced-visual-quality_603293",
      "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 AIGC 创作工作流**：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。",
        "当前公开的是试用入口、样例质量、版权边界、价格信息和生产可用范围。",
        "这会影响内容团队判断创作工具能否进入正式生产流程、预算清单和版权审查。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Meta Newsroom: Meta Essilorluxottica Partner Launch Meta Glasses",
      "editorial_category": "product_radar",
      "event_date": "2026-06-23",
      "url": "https://about.fb.com/news/2026/06/meta-essilorluxottica-partner-launch-meta-glasses/",
      "source": "Meta Newsroom",
      "tier": "T0",
      "entities": [
        "Meta Newsroom"
      ],
      "summary": "Meta Newsroom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": [
        "**Meta Newsroom更新AI 产品、平台或工程实践**：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。",
        "当前公开的是产品入口、适用对象、价格地区限制、权限要求和后续上线节奏。",
        "这会改变产品和采购团队安排试用、预算审批、替换工具和风险复盘的优先级。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Alibaba Cloud发布 Claude Code agent 工具工作流",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-24",
      "url": "https://www.alibabacloud.com/blog/alibaba-cloud-releases-anolisa-agentic-os-the-first-agent-oriented-operating-system_603295",
      "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发布 Claude Code**：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": "OpenAI公布模型评估和研究结果",
      "editorial_category": "ai_industry",
      "event_date": "2026-06-23",
      "url": "https://openai.com/index/gpt-5-immunology-mystery",
      "source": "OpenAI News RSS",
      "tier": "T0",
      "entities": [
        "OpenAI News RSS"
      ],
      "summary": "OpenAI披露模型能力和评估方法更新，材料覆盖能力边界、评估设置、数据来源、使用场景和限制说明，边界落在结论仍要依赖可复现评测、真实任务和公开限制。",
      "bullets": [
        "**OpenAI披露模型评估和研究结果**：材料把模型能力和评估方法更新落到能力边界、评估设置、数据来源、使用场景和限制说明，已披露事实集中在模型能力、评估设置、数据来源和限制说明。",
        "当前公开的是实验设置、数据范围、对比基线、复现材料和作者承认的限制。",
        "这会改变模型和平台团队对能力边界、推理成本、可靠性和内部实验设计的预期。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Alibaba Cloud更新agent 与开发者工具能力",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-23",
      "url": "https://www.alibabacloud.com/blog/cross-platform-quant-trading-bringing-smart-q-into-market-monitoring-and-trading-review_603291",
      "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": "OpenAI说明安全治理和平台控制变化",
      "editorial_category": "ai_industry",
      "event_date": "2026-06-23",
      "url": "https://openai.com/index/helping-build-shared-standards-for-advanced-ai",
      "source": "OpenAI News RSS",
      "tier": "T0",
      "entities": [
        "OpenAI News RSS"
      ],
      "summary": "OpenAI披露模型能力和评估方法更新，材料覆盖能力边界、评估设置、数据来源、使用场景和限制说明，边界落在结论仍要依赖可复现评测、真实任务和公开限制。",
      "bullets": [
        "**OpenAI披露安全治理和平台控制变化**：材料把模型能力和评估方法更新落到能力边界、评估设置、数据来源、使用场景和限制说明，已披露事实集中在模型能力、评估设置、数据来源和限制说明。",
        "当前公开的是实验设置、数据范围、对比基线、复现材料和作者承认的限制。",
        "这会改变模型和平台团队对能力边界、推理成本、可靠性和内部实验设计的预期。"
      ],
      "importance": "general",
      "image_urls": []
    },
    {
      "title": "Google发布 AIGC 创作工作流",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-23",
      "url": "https://blog.google/company-news/inside-google/around-the-globe/google-europe/preserving-cultural-heritage-inside-google-deepminds-collaboration-with-pele/",
      "source": "Google Keyword Blog",
      "tier": "T0",
      "entities": [
        "Google Keyword Blog"
      ],
      "summary": "DeepMind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": [
        "**Google披露 AIGC 创作工作流**：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": "Microsoft更新agent 可观测平台更新",
      "editorial_category": "engineering_toolchain",
      "event_date": "2026-06-23",
      "url": "https://blogs.microsoft.com/blog/2026/06/23/rethinking-cloud-operations-with-agentic-observability/",
      "source": "Official Microsoft Blog",
      "tier": "T0",
      "entities": [
        "Official Microsoft Blog"
      ],
      "summary": "微软研究院发布生产 agent 观测面板，材料覆盖工具调用轨迹、事故时间线、成本归因、回滚状态和发布健康度，边界落在观测价值取决于能否把失败记录、成本和发布状态串进同一条链路。",
      "bullets": [
        "**Microsoft披露 agent 可观测平台更新**：材料把生产 agent 观测面板落到工具调用轨迹、事故时间线、成本归因、回滚状态和发布健康度，已披露事实集中在tool-call traces、事故记录、成本归因和回滚状态。",
        "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": []
    }
  ],
  "github_trending": [
    {
      "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": "2026-06-24",
      "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": "DeusData/codebase-memory-mcp 本周出现在开源榜单 weekly #1，本周 +8,536 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": "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": "2026-06-24",
      "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": "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": "google-research/timesfm",
      "repo": "google-research/timesfm",
      "readme_cache": {
        "key": "github-readme/google-research/timesfm/master/unknown",
        "hit": true,
        "repo": "google-research/timesfm",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/google-research/timesfm/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/google-research/timesfm",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 3,
      "source_rank": 3,
      "source_scope": "weekly:all",
      "previous_rank": 5,
      "rank_delta": 2,
      "trend": "up",
      "importance": "notable",
      "description": "google-research/timesfm 本周出现在开源榜单 weekly #3，本周 +4,376 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": "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": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 4,
      "source_rank": 4,
      "source_scope": "weekly:all",
      "previous_rank": 3,
      "rank_delta": -1,
      "trend": "down",
      "importance": "general",
      "description": "Panniantong/Agent-Reach 本周出现在开源榜单 weekly #4，本周 +6,915 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": "n0-computer/iroh",
      "repo": "n0-computer/iroh",
      "readme_cache": {
        "key": "github-readme/n0-computer/iroh/main/unknown",
        "hit": true,
        "repo": "n0-computer/iroh",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/n0-computer/iroh/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/n0-computer/iroh",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 5,
      "source_rank": 5,
      "source_scope": "weekly:all",
      "previous_rank": 4,
      "rank_delta": -1,
      "trend": "down",
      "importance": "general",
      "description": "n0-computer/iroh 本周出现在开源榜单 weekly #5，本周 +1,531 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": "asgeirtj/system_prompts_leaks",
      "repo": "asgeirtj/system_prompts_leaks",
      "readme_cache": {
        "key": "github-readme/asgeirtj/system_prompts_leaks/main/unknown",
        "hit": true,
        "repo": "asgeirtj/system_prompts_leaks",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/asgeirtj/system_prompts_leaks/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/asgeirtj/system_prompts_leaks",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 6,
      "source_rank": 6,
      "source_scope": "weekly:all",
      "previous_rank": 7,
      "rank_delta": 1,
      "trend": "up",
      "importance": "general",
      "description": "asgeirtj/system_prompts_leaks 本周出现在开源榜单 weekly #6，本周 +2,681 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": "koala73/worldmonitor",
      "repo": "koala73/worldmonitor",
      "readme_cache": {
        "key": "github-readme/koala73/worldmonitor/main/unknown",
        "hit": true,
        "repo": "koala73/worldmonitor",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/koala73/worldmonitor/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/koala73/worldmonitor",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 7,
      "source_rank": 7,
      "source_scope": "weekly:all",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "koala73/worldmonitor 本周出现在开源榜单 weekly #7，本周 +2,309 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": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 8,
      "source_rank": 8,
      "source_scope": "weekly:all",
      "previous_rank": 6,
      "rank_delta": -2,
      "trend": "down",
      "importance": "general",
      "description": "iptv-org/iptv 本周出现在开源榜单 weekly #8，本周 +4,378 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": "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": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 9,
      "source_rank": 9,
      "source_scope": "weekly:all",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "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": "withastro/flue",
      "repo": "withastro/flue",
      "readme_cache": {
        "key": "github-readme/withastro/flue/main/unknown",
        "hit": true,
        "repo": "withastro/flue",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/withastro/flue/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/withastro/flue",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "language": "all",
      "window": "weekly",
      "rank": 10,
      "source_rank": 10,
      "source_scope": "weekly:all",
      "previous_rank": 8,
      "rank_delta": -2,
      "trend": "down",
      "importance": "general",
      "description": "withastro/flue 本周出现在开源榜单 weekly #10，本周 +1,489 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": "LMCache/LMCache",
      "repo": "LMCache/LMCache",
      "readme_cache": {
        "key": "github-readme/lmcache/lmcache/main/unknown",
        "hit": true,
        "repo": "lmcache/lmcache",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/LMCache/LMCache/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/LMCache/LMCache",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Python weekly",
      "language": "python",
      "window": "weekly",
      "rank": 11,
      "source_rank": 5,
      "source_scope": "weekly:python",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "LMCache/LMCache 本周出现在开源榜单 Python weekly #11，本周 +537 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": "RocketChat/Rocket.Chat",
      "repo": "RocketChat/Rocket.Chat",
      "readme_cache": {
        "key": "github-readme/rocketchat/rocket.chat/master/unknown",
        "hit": true,
        "repo": "rocketchat/rocket.chat",
        "sha": "unknown",
        "default_branch": "master",
        "source_url": "https://raw.githubusercontent.com/RocketChat/Rocket.Chat/master/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/RocketChat/Rocket.Chat",
      "event_date": "2026-06-24",
      "source": "GitHub Trending TypeScript weekly",
      "language": "typescript",
      "window": "weekly",
      "rank": 12,
      "source_rank": 11,
      "source_scope": "weekly:typescript",
      "previous_rank": 13,
      "rank_delta": 2,
      "trend": "up",
      "importance": "general",
      "description": "RocketChat/Rocket.Chat 本周出现在开源榜单 TypeScript weekly #12，本周 +240 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": "2026-06-24",
      "source": "GitHub Trending Rust weekly",
      "language": "rust",
      "window": "weekly",
      "rank": 13,
      "source_rank": 2,
      "source_scope": "weekly:rust",
      "previous_rank": 4,
      "rank_delta": 2,
      "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": "cilium/cilium",
      "repo": "cilium/cilium",
      "readme_fetch_status": "failed",
      "readme_error": "HTTP 404",
      "url": "https://github.com/cilium/cilium",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Go weekly",
      "language": "go",
      "window": "weekly",
      "rank": 14,
      "source_rank": 1,
      "source_scope": "weekly:go",
      "previous_rank": 4,
      "rank_delta": 3,
      "trend": "up",
      "importance": "general",
      "description": "cilium/cilium 本周出现在开源榜单 Go weekly #14，本周 +76 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": "AutoMQ/automq",
      "repo": "AutoMQ/automq",
      "readme_cache": {
        "key": "github-readme/automq/automq/main/unknown",
        "hit": true,
        "repo": "automq/automq",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/AutoMQ/automq/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/AutoMQ/automq",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Java weekly",
      "language": "java",
      "window": "weekly",
      "rank": 15,
      "source_rank": 1,
      "source_scope": "weekly:java",
      "previous_rank": 5,
      "rank_delta": 4,
      "trend": "up",
      "importance": "general",
      "description": "AutoMQ/automq 本周出现在开源榜单 Java weekly #15，本周 +78 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": "mukul975/Anthropic-Cybersecurity-Skills",
      "repo": "mukul975/Anthropic-Cybersecurity-Skills",
      "readme_cache": {
        "key": "github-readme/mukul975/anthropic-cybersecurity-skills/main/unknown",
        "hit": true,
        "repo": "mukul975/anthropic-cybersecurity-skills",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/mukul975/Anthropic-Cybersecurity-Skills",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Python weekly",
      "language": "python",
      "window": "weekly",
      "rank": 16,
      "source_rank": 6,
      "source_scope": "weekly:python",
      "previous_rank": null,
      "rank_delta": null,
      "trend": "new",
      "importance": "general",
      "description": "mukul975/Anthropic-Cybersecurity-Skills 本周出现在开源榜单 Python weekly #16，本周 +3,456 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": "Kilo-Org/kilocode",
      "repo": "Kilo-Org/kilocode",
      "readme_cache": {
        "key": "github-readme/kilo-org/kilocode/main/unknown",
        "hit": true,
        "repo": "kilo-org/kilocode",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/Kilo-Org/kilocode/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/Kilo-Org/kilocode",
      "event_date": "2026-06-24",
      "source": "GitHub Trending TypeScript weekly",
      "language": "typescript",
      "window": "weekly",
      "rank": 17,
      "source_rank": 12,
      "source_scope": "weekly:typescript",
      "previous_rank": 12,
      "rank_delta": 0,
      "trend": "same",
      "importance": "general",
      "description": "Kilo-Org/kilocode 本周出现在开源榜单 TypeScript weekly #17，本周 +4,206 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": "Universal-Debloater-Alliance/universal-android-debloater-next-generation",
      "repo": "Universal-Debloater-Alliance/universal-android-debloater-next-generation",
      "readme_cache": {
        "key": "github-readme/universal-debloater-alliance/universal-android-debloater-next-generation/main/unknown",
        "hit": true,
        "repo": "universal-debloater-alliance/universal-android-debloater-next-generation",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/Universal-Debloater-Alliance/universal-android-debloater-next-generation/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/Universal-Debloater-Alliance/universal-android-debloater-next-generation",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Rust weekly",
      "language": "rust",
      "window": "weekly",
      "rank": 18,
      "source_rank": 3,
      "source_scope": "weekly:rust",
      "previous_rank": 18,
      "rank_delta": 15,
      "trend": "up",
      "importance": "general",
      "description": "Universal-Debloater-Alliance/universal-android-debloater-next-generation 本周出现在开源榜单 Rust weekly #18，本周 +961 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": "everywall/ladder",
      "repo": "everywall/ladder",
      "readme_cache": {
        "key": "github-readme/everywall/ladder/main/unknown",
        "hit": true,
        "repo": "everywall/ladder",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/everywall/ladder/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/everywall/ladder",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Go weekly",
      "language": "go",
      "window": "weekly",
      "rank": 19,
      "source_rank": 2,
      "source_scope": "weekly:go",
      "previous_rank": 19,
      "rank_delta": 17,
      "trend": "up",
      "importance": "general",
      "description": "everywall/ladder 本周出现在开源榜单 Go weekly #19，本周 +480 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": "krahets/hello-algo",
      "repo": "krahets/hello-algo",
      "readme_cache": {
        "key": "github-readme/krahets/hello-algo/main/unknown",
        "hit": true,
        "repo": "krahets/hello-algo",
        "sha": "unknown",
        "default_branch": "main",
        "source_url": "https://raw.githubusercontent.com/krahets/hello-algo/main/README.md"
      },
      "readme_fetch_status": "ok",
      "url": "https://github.com/krahets/hello-algo",
      "event_date": "2026-06-24",
      "source": "GitHub Trending Java weekly",
      "language": "java",
      "window": "weekly",
      "rank": 20,
      "source_rank": 2,
      "source_scope": "weekly:java",
      "previous_rank": 3,
      "rank_delta": 1,
      "trend": "up",
      "importance": "general",
      "description": "krahets/hello-algo 本周出现在开源榜单 Java weekly #20，本周 +670 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": [],
  "model_releases": [],
  "hot_blogs": [
    {
      "title": "相关团队更新agent 工作流和开发工具能力",
      "editorial_category": "viewpoint_analysis",
      "image_url": "https://cdn-avatars.huggingface.co/v1/production/uploads/62dc173789b4cf157d36ebee/i_pxzM2ZDo3Ub-BEgIkE9.png",
      "image_alt": "zai-org/SCAIL-2",
      "image_source": "html_index",
      "url": "https://huggingface.co/zai-org/SCAIL-2",
      "publisher": "Z.ai Hugging Face Organization",
      "author": "Z.ai Hugging Face Organization",
      "event_date": "2026-06-22",
      "topic": "AI industry",
      "summary": "相关团队更新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。",
      "content_type": "blog",
      "importance": "notable",
      "image_urls": []
    },
    {
      "title": "Meta Engineering更新AI 产品、平台或工程实践",
      "editorial_category": "viewpoint_analysis",
      "url": "https://engineering.fb.com/2026/06/23/production-engineering/how-meta-built-ultra-narrow-batteries-for-ai-glasses-meta-tech-podcast/",
      "publisher": "Meta Engineering",
      "author": "Meta Engineering",
      "event_date": "2026-06-23",
      "topic": "AI industry",
      "summary": "Meta Engineering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": []
    },
    {
      "title": "苹果机器学习研究团队披露模型评估和研究结果",
      "editorial_category": "viewpoint_analysis",
      "url": "https://machinelearning.apple.com/research/metric-dependent-annotation-saturation",
      "publisher": "Apple Machine Learning Research",
      "author": "Apple Machine Learning Research",
      "event_date": "2026-06-23",
      "topic": "research / evaluation",
      "summary": "Apple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": "NVIDIA披露 agent 与开发者工具能力",
      "editorial_category": "viewpoint_analysis",
      "image_url": "https://iprsoftwaremedia.com/219/files/202606/72236eb3cbeb9d0e06fdbd0a08dadf31/6a3a837f3d633232493bcf6b_agentic-ai-agent-toolkit-kv-r3b-1920x1080-2-842x450/agentic-ai-agent-toolkit-kv-r3b-1920x1080-2-842x450_thmb.jpg",
      "image_alt": "How Businesses Are Building Specialized AI They Can Trust",
      "image_source": "feed",
      "url": "https://blogs.nvidia.com/blog/nvidia-agent-toolkit-open-models-tools-skills-secure-runtime-ai-agents/",
      "publisher": "NVIDIA Newsroom RSS",
      "author": "NVIDIA Newsroom RSS",
      "event_date": "2026-06-23",
      "topic": "AI industry",
      "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": "NVIDIA披露模型评估和研究结果",
      "editorial_category": "viewpoint_analysis",
      "url": "https://developer.nvidia.com/blog/build-an-ai-scientist-for-life-science-discovery-with-nvidia-bionemo-agent-toolkit/",
      "publisher": "NVIDIA Developer Blog",
      "author": "NVIDIA Developer Blog",
      "event_date": "2026-06-23",
      "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": "NVIDIA披露具体的 agent 工作流更新，面向开发团队",
      "editorial_category": "viewpoint_analysis",
      "url": "https://developer.nvidia.com/blog/boost-inference-performance-up-to-15x-on-nvidia-blackwell-using-dflash-speculative-decoding/",
      "publisher": "NVIDIA Developer Blog",
      "author": "NVIDIA Developer Blog",
      "event_date": "2026-06-23",
      "topic": "AI engineering tools",
      "summary": "NVIDIA说明SageMaker 推测解码并行化方案，重点落在draft model 并行、解码延迟、吞吐取舍、部署设置和适用条件。更有价值的信息是P-EAGLE、speculative decoding、SageMaker 部署和吞吐延迟指标，判断这类方案时还要看优化收益取决于模型结构、请求形态、草稿模型质量和线上延迟预算。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": "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/news-insights/policy-news-and-insights/github-joins-coalition-advocating-for-fixes-to-california-ai-transparency-act-to-protect-open-source/",
      "publisher": "GitHub Blog Feed",
      "author": "GitHub Blog Feed",
      "event_date": "2026-06-23",
      "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": []
    }
  ],
  "chinese_media_dynamics": [
    {
      "title": "智能座舱之王「转身」物理AI，高通需要被重估了",
      "url": "https://www.qbitai.com/2026/06/432494.html",
      "publisher": "QbitAI",
      "author": "QbitAI",
      "event_date": "2026-06-24",
      "topic": "中文 AI 媒体动态",
      "summary": "智能座舱之王「转身」物理AI，高通需要被重估了：不争最强算力，只求无处不在。",
      "key_points": [
        "智能座舱之王「转身」物理AI，高通需要被重估了：不争最强算力，只求无处不在",
        "This is an intermediary/self-media lead; trace it to a primary source before treating it as a reported fact."
      ],
      "importance": "notable",
      "image_urls": []
    }
  ],
  "daily_tracking": [
    {
      "id": "openrouter-rankings",
      "name": "OpenRouter",
      "url": "https://openrouter.ai/rankings",
      "event_date": "2026-06-24",
      "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 4.94T tokens；#2 MiMo-V2.5 4.28T tokens；#3 MiniMax M3 3.76T tokens；Claude Opus 4.8 周变化 43%。",
      "summary": "OpenRouter 公开榜单显示，本周调用热度第一是 DeepSeek V4 Flash（deepseek，4.94T tokens，周变化 12%）。 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": [
        "Claude Opus 4.8 的周变化为 43%，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）：4.94T tokens，周变化 12%",
          "trend": "up"
        },
        {
          "label": "#2",
          "value": "MiMo-V2.5（xiaomi）：4.28T tokens，周变化 17%",
          "trend": "up"
        },
        {
          "label": "#3",
          "value": "MiniMax M3（minimax）：3.76T tokens，周变化 19%",
          "trend": "up"
        },
        {
          "label": "#4",
          "value": "Hy3 preview（tencent）：3.6T tokens，周变化 6%",
          "trend": "up"
        },
        {
          "label": "#5",
          "value": "Owl Alpha（openrouter）：2.78T tokens，周变化 14%",
          "trend": "up"
        },
        {
          "label": "#6",
          "value": "Claude Opus 4.7（anthropic）：2.48T tokens，周变化 8%",
          "trend": "up"
        },
        {
          "label": "#7",
          "value": "DeepSeek V4 Pro（deepseek）：2.34T tokens，周变化 19%",
          "trend": "up"
        },
        {
          "label": "#8",
          "value": "Claude Opus 4.8（anthropic）：1.82T tokens，周变化 43%",
          "trend": "up"
        },
        {
          "label": "#9",
          "value": "GLM 5.2（z-ai）：1.77T tokens，周变化 >999%",
          "trend": "unknown"
        },
        {
          "label": "#10",
          "value": "Claude Sonnet 4.6（anthropic）：1.52T tokens，周变化 19%",
          "trend": "up"
        }
      ],
      "snapshot": {
        "type": "openrouter_rankings_public_page",
        "collection_method": "public_page_playwright",
        "snapshot_status": "complete",
        "snapshot_as_of": "2026-06-24T02:31:25.210Z",
        "source_url": "https://openrouter.ai/rankings",
        "top_entries": [
          {
            "rank": 1,
            "model": "DeepSeek V4 Flash",
            "provider": "deepseek",
            "tokens": "4.94T tokens",
            "change": "12%"
          },
          {
            "rank": 2,
            "model": "MiMo-V2.5",
            "provider": "xiaomi",
            "tokens": "4.28T tokens",
            "change": "17%"
          },
          {
            "rank": 3,
            "model": "MiniMax M3",
            "provider": "minimax",
            "tokens": "3.76T tokens",
            "change": "19%"
          },
          {
            "rank": 4,
            "model": "Hy3 preview",
            "provider": "tencent",
            "tokens": "3.6T tokens",
            "change": "6%"
          },
          {
            "rank": 5,
            "model": "Owl Alpha",
            "provider": "openrouter",
            "tokens": "2.78T tokens",
            "change": "14%"
          },
          {
            "rank": 6,
            "model": "Claude Opus 4.7",
            "provider": "anthropic",
            "tokens": "2.48T tokens",
            "change": "8%"
          },
          {
            "rank": 7,
            "model": "DeepSeek V4 Pro",
            "provider": "deepseek",
            "tokens": "2.34T tokens",
            "change": "19%"
          },
          {
            "rank": 8,
            "model": "Claude Opus 4.8",
            "provider": "anthropic",
            "tokens": "1.82T tokens",
            "change": "43%"
          },
          {
            "rank": 9,
            "model": "GLM 5.2",
            "provider": "z-ai",
            "tokens": "1.77T tokens",
            "change": ">999%"
          },
          {
            "rank": 10,
            "model": "Claude Sonnet 4.6",
            "provider": "anthropic",
            "tokens": "1.52T tokens",
            "change": "19%"
          }
        ],
        "official_component_snapshot": {
          "source": "official_dom",
          "component_kind": "openrouter_rankings",
          "source_url": "https://openrouter.ai/rankings",
          "captured_at": "2026-06-24T02:31:25.210Z",
          "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>4.94T tokens</td><td>12%</td></tr>\n        <tr><td>#2</td><td>MiMo-V2.5</td><td>xiaomi</td><td>4.28T tokens</td><td>17%</td></tr>\n        <tr><td>#3</td><td>MiniMax M3</td><td>minimax</td><td>3.76T tokens</td><td>19%</td></tr>\n        <tr><td>#4</td><td>Hy3 preview</td><td>tencent</td><td>3.6T tokens</td><td>6%</td></tr>\n        <tr><td>#5</td><td>Owl Alpha</td><td>openrouter</td><td>2.78T tokens</td><td>14%</td></tr>\n        <tr><td>#6</td><td>Claude Opus 4.7</td><td>anthropic</td><td>2.48T tokens</td><td>8%</td></tr>\n        <tr><td>#7</td><td>DeepSeek V4 Pro</td><td>deepseek</td><td>2.34T tokens</td><td>19%</td></tr>\n        <tr><td>#8</td><td>Claude Opus 4.8</td><td>anthropic</td><td>1.82T tokens</td><td>43%</td></tr>\n        <tr><td>#9</td><td>GLM 5.2</td><td>z-ai</td><td>1.77T tokens</td><td>&gt;999%</td></tr>\n        <tr><td>#10</td><td>Claude Sonnet 4.6</td><td>anthropic</td><td>1.52T tokens</td><td>19%</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:b39404be1b1edf86703b974d4225c6cb10ebb9101b7cbd4cc089d7d103de56ec",
          "css_hash": "sha256:e5df3dc0e07de42f5c2ca4021bbf59258d47d1ef0fa569d55d98b09876618e43"
        },
        "history_entries": []
      },
      "tracking_component_snapshot": {
        "source": "OpenRouter",
        "component_kind": "openrouter_rankings",
        "source_url": "https://openrouter.ai/rankings",
        "collected_at": "2026-06-24T02:31:25.210Z",
        "selector_version": "openrouter-rankings-v1",
        "raw_dom_hash": "sha256:0ed9a75c24b28fec5199ed263b166efd637f6357c112cc5e04f49896fa8d695f",
        "data_hash": "sha256:fcd7ec386af95b1b1746462a1d2515ea4a6527caf5a79e19c4c40f1b6a352c59",
        "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": 4940000000000,
                "value_label": "4.94T tokens",
                "change": "12%"
              },
              {
                "rank": 2,
                "model": "MiMo-V2.5",
                "provider": "xiaomi",
                "value": 4280000000000.0005,
                "value_label": "4.28T tokens",
                "change": "17%"
              },
              {
                "rank": 3,
                "model": "MiniMax M3",
                "provider": "minimax",
                "value": 3760000000000,
                "value_label": "3.76T tokens",
                "change": "19%"
              },
              {
                "rank": 4,
                "model": "Hy3 preview",
                "provider": "tencent",
                "value": 3600000000000,
                "value_label": "3.6T tokens",
                "change": "6%"
              },
              {
                "rank": 5,
                "model": "Owl Alpha",
                "provider": "openrouter",
                "value": 2780000000000,
                "value_label": "2.78T tokens",
                "change": "14%"
              },
              {
                "rank": 6,
                "model": "Claude Opus 4.7",
                "provider": "anthropic",
                "value": 2480000000000,
                "value_label": "2.48T tokens",
                "change": "8%"
              },
              {
                "rank": 7,
                "model": "DeepSeek V4 Pro",
                "provider": "deepseek",
                "value": 2340000000000,
                "value_label": "2.34T tokens",
                "change": "19%"
              },
              {
                "rank": 8,
                "model": "Claude Opus 4.8",
                "provider": "anthropic",
                "value": 1820000000000,
                "value_label": "1.82T tokens",
                "change": "43%"
              },
              {
                "rank": 9,
                "model": "GLM 5.2",
                "provider": "z-ai",
                "value": 1770000000000,
                "value_label": "1.77T tokens",
                "change": ">999%"
              },
              {
                "rank": 10,
                "model": "Claude Sonnet 4.6",
                "provider": "anthropic",
                "value": 1520000000000,
                "value_label": "1.52T tokens",
                "change": "19%"
              }
            ],
            "fallback_reason": ""
          },
          {
            "id": "openrouter-llm-leaderboard",
            "tab_id": "leaderboard",
            "label": "LLM Leaderboard",
            "chart": "leaderboard",
            "rows": [
              {
                "rank": 1,
                "model": "DeepSeek V4 Flash",
                "provider": "deepseek",
                "value": 4940000000000,
                "value_label": "4.94T tokens",
                "change": "12%"
              },
              {
                "rank": 2,
                "model": "MiMo-V2.5",
                "provider": "xiaomi",
                "value": 4280000000000.0005,
                "value_label": "4.28T tokens",
                "change": "17%"
              },
              {
                "rank": 3,
                "model": "MiniMax M3",
                "provider": "minimax",
                "value": 3760000000000,
                "value_label": "3.76T tokens",
                "change": "19%"
              },
              {
                "rank": 4,
                "model": "Hy3 preview",
                "provider": "tencent",
                "value": 3600000000000,
                "value_label": "3.6T tokens",
                "change": "6%"
              },
              {
                "rank": 5,
                "model": "Owl Alpha",
                "provider": "openrouter",
                "value": 2780000000000,
                "value_label": "2.78T tokens",
                "change": "14%"
              },
              {
                "rank": 6,
                "model": "Claude Opus 4.7",
                "provider": "anthropic",
                "value": 2480000000000,
                "value_label": "2.48T tokens",
                "change": "8%"
              },
              {
                "rank": 7,
                "model": "DeepSeek V4 Pro",
                "provider": "deepseek",
                "value": 2340000000000,
                "value_label": "2.34T tokens",
                "change": "19%"
              },
              {
                "rank": 8,
                "model": "Claude Opus 4.8",
                "provider": "anthropic",
                "value": 1820000000000,
                "value_label": "1.82T tokens",
                "change": "43%"
              },
              {
                "rank": 9,
                "model": "GLM 5.2",
                "provider": "z-ai",
                "value": 1770000000000,
                "value_label": "1.77T tokens",
                "change": ">999%"
              },
              {
                "rank": 10,
                "model": "Claude Sonnet 4.6",
                "provider": "anthropic",
                "value": 1520000000000,
                "value_label": "1.52T tokens",
                "change": "19%"
              }
            ],
            "fallback_reason": ""
          }
        ],
        "rows": [
          {
            "rank": 1,
            "model": "DeepSeek V4 Flash",
            "provider": "deepseek",
            "value": 4940000000000,
            "value_label": "4.94T tokens",
            "change": "12%"
          },
          {
            "rank": 2,
            "model": "MiMo-V2.5",
            "provider": "xiaomi",
            "value": 4280000000000.0005,
            "value_label": "4.28T tokens",
            "change": "17%"
          },
          {
            "rank": 3,
            "model": "MiniMax M3",
            "provider": "minimax",
            "value": 3760000000000,
            "value_label": "3.76T tokens",
            "change": "19%"
          },
          {
            "rank": 4,
            "model": "Hy3 preview",
            "provider": "tencent",
            "value": 3600000000000,
            "value_label": "3.6T tokens",
            "change": "6%"
          },
          {
            "rank": 5,
            "model": "Owl Alpha",
            "provider": "openrouter",
            "value": 2780000000000,
            "value_label": "2.78T tokens",
            "change": "14%"
          },
          {
            "rank": 6,
            "model": "Claude Opus 4.7",
            "provider": "anthropic",
            "value": 2480000000000,
            "value_label": "2.48T tokens",
            "change": "8%"
          },
          {
            "rank": 7,
            "model": "DeepSeek V4 Pro",
            "provider": "deepseek",
            "value": 2340000000000,
            "value_label": "2.34T tokens",
            "change": "19%"
          },
          {
            "rank": 8,
            "model": "Claude Opus 4.8",
            "provider": "anthropic",
            "value": 1820000000000,
            "value_label": "1.82T tokens",
            "change": "43%"
          },
          {
            "rank": 9,
            "model": "GLM 5.2",
            "provider": "z-ai",
            "value": 1770000000000,
            "value_label": "1.77T tokens",
            "change": ">999%"
          },
          {
            "rank": 10,
            "model": "Claude Sonnet 4.6",
            "provider": "anthropic",
            "value": 1520000000000,
            "value_label": "1.52T tokens",
            "change": "19%"
          }
        ],
        "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",
            "Hy3 preview",
            "Owl Alpha",
            "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": "2026-06-24T02:31:25.210Z",
          "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>4.94T tokens</td><td>12%</td></tr>\n        <tr><td>#2</td><td>MiMo-V2.5</td><td>xiaomi</td><td>4.28T tokens</td><td>17%</td></tr>\n        <tr><td>#3</td><td>MiniMax M3</td><td>minimax</td><td>3.76T tokens</td><td>19%</td></tr>\n        <tr><td>#4</td><td>Hy3 preview</td><td>tencent</td><td>3.6T tokens</td><td>6%</td></tr>\n        <tr><td>#5</td><td>Owl Alpha</td><td>openrouter</td><td>2.78T tokens</td><td>14%</td></tr>\n        <tr><td>#6</td><td>Claude Opus 4.7</td><td>anthropic</td><td>2.48T tokens</td><td>8%</td></tr>\n        <tr><td>#7</td><td>DeepSeek V4 Pro</td><td>deepseek</td><td>2.34T tokens</td><td>19%</td></tr>\n        <tr><td>#8</td><td>Claude Opus 4.8</td><td>anthropic</td><td>1.82T tokens</td><td>43%</td></tr>\n        <tr><td>#9</td><td>GLM 5.2</td><td>z-ai</td><td>1.77T tokens</td><td>&gt;999%</td></tr>\n        <tr><td>#10</td><td>Claude Sonnet 4.6</td><td>anthropic</td><td>1.52T tokens</td><td>19%</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:b39404be1b1edf86703b974d4225c6cb10ebb9101b7cbd4cc089d7d103de56ec",
          "css_hash": "sha256:e5df3dc0e07de42f5c2ca4021bbf59258d47d1ef0fa569d55d98b09876618e43"
        },
        "public_trace": {
          "source_url": "https://openrouter.ai/rankings",
          "collected_at": "2026-06-24T02:31:25.210Z",
          "selector_version": "openrouter-rankings-v1",
          "data_hash": "sha256:fcd7ec386af95b1b1746462a1d2515ea4a6527caf5a79e19c4c40f1b6a352c59",
          "top_rows": [
            {
              "rank": 1,
              "model": "DeepSeek V4 Flash",
              "provider": "deepseek",
              "value_label": "4.94T tokens",
              "change": "12%"
            },
            {
              "rank": 2,
              "model": "MiMo-V2.5",
              "provider": "xiaomi",
              "value_label": "4.28T tokens",
              "change": "17%"
            },
            {
              "rank": 3,
              "model": "MiniMax M3",
              "provider": "minimax",
              "value_label": "3.76T tokens",
              "change": "19%"
            },
            {
              "rank": 4,
              "model": "Hy3 preview",
              "provider": "tencent",
              "value_label": "3.6T tokens",
              "change": "6%"
            },
            {
              "rank": 5,
              "model": "Owl Alpha",
              "provider": "openrouter",
              "value_label": "2.78T tokens",
              "change": "14%"
            },
            {
              "rank": 6,
              "model": "Claude Opus 4.7",
              "provider": "anthropic",
              "value_label": "2.48T tokens",
              "change": "8%"
            },
            {
              "rank": 7,
              "model": "DeepSeek V4 Pro",
              "provider": "deepseek",
              "value_label": "2.34T tokens",
              "change": "19%"
            },
            {
              "rank": 8,
              "model": "Claude Opus 4.8",
              "provider": "anthropic",
              "value_label": "1.82T tokens",
              "change": "43%"
            },
            {
              "rank": 9,
              "model": "GLM 5.2",
              "provider": "z-ai",
              "value_label": "1.77T tokens",
              "change": ">999%"
            },
            {
              "rank": 10,
              "model": "Claude Sonnet 4.6",
              "provider": "anthropic",
              "value_label": "1.52T tokens",
              "change": "19%"
            }
          ],
          "diff": {
            "summary": "No previous component snapshot was available for comparison.",
            "changed_rows": [],
            "new_entries": [
              "DeepSeek V4 Flash",
              "MiMo-V2.5",
              "MiniMax M3",
              "Hy3 preview",
              "Owl Alpha",
              "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": "2026-06-24",
      "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": "2026-06-24T02:31:25.210Z",
        "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": "2026-06-24T02:31:25.210Z",
          "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": "2026-06-24T02:31:25.210Z",
        "selector_version": "artificial-analysis-index-v1",
        "raw_dom_hash": "sha256:caa7d33c2116c5495c0ff87bb3af671e33346e063be109cb1e5beccdf50e227a",
        "data_hash": "sha256:67ad25852a55593f54d215048138d2296986c491d48f91829978a12ca43470a0",
        "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": "2026-06-24T02:31:25.210Z",
          "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": "2026-06-24T02:31:25.210Z",
          "selector_version": "artificial-analysis-index-v1",
          "data_hash": "sha256:67ad25852a55593f54d215048138d2296986c491d48f91829978a12ca43470a0",
          "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": "2026-06-24",
      "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": "2026-06-24T02:31:25.210Z",
        "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": "2026-06-24T02:31:25.210Z",
          "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": "2026-06-24T02:31:25.210Z",
        "selector_version": "swe-bench-pro-v1",
        "raw_dom_hash": "sha256:2d5ebf88219cf9ca3b8537c2a99a9339988bd6f4b8cb73e80b37c9c1e786a9a9",
        "data_hash": "sha256:9fe0d2176123396723524bdb517563546b5cd3706e9a562a35ad1e16180b4fc3",
        "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": "2026-06-24T02:31:25.210Z",
          "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": "2026-06-24T02:31:25.210Z",
          "selector_version": "swe-bench-pro-v1",
          "data_hash": "sha256:9fe0d2176123396723524bdb517563546b5cd3706e9a562a35ad1e16180b4fc3",
          "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": "DeusData/codebase-memory-mcp",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/DeusData/codebase-memory-mcp",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "calesthio/OpenMontage",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/calesthio/OpenMontage",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "google-research/timesfm",
      "editorial_category": "open_source",
      "domains": [
        "AI tooling"
      ],
      "url": "https://github.com/google-research/timesfm",
      "event_date": "2026-06-24",
      "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": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "n0-computer/iroh",
      "editorial_category": "open_source",
      "domains": [
        "AI tooling"
      ],
      "url": "https://github.com/n0-computer/iroh",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "asgeirtj/system_prompts_leaks",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/asgeirtj/system_prompts_leaks",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "koala73/worldmonitor",
      "editorial_category": "open_source",
      "domains": [
        "AI tooling"
      ],
      "url": "https://github.com/koala73/worldmonitor",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "iptv-org/iptv",
      "editorial_category": "open_source",
      "domains": [
        "AI tooling"
      ],
      "url": "https://github.com/iptv-org/iptv",
      "event_date": "2026-06-24",
      "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": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    },
    {
      "name": "withastro/flue",
      "editorial_category": "open_source",
      "domains": [
        "agent"
      ],
      "url": "https://github.com/withastro/flue",
      "event_date": "2026-06-24",
      "source": "GitHub Trending weekly",
      "signal": "trending",
      "importance": "notable"
    }
  ],
  "builder_observations": [
    {
      "author": "Thibault Sottiaux",
      "handle": "thsottiaux",
      "editorial_category": "x_discussion",
      "content": "让我们一起给整个星球打补丁。Codex 安全能力迎来更新，同时发布新的 GPT-5.5-Cyber；这是为网络防御加速庆祝的一天。",
      "original_text": "Let's Patch The Planet. Updates to codex security and a new GPT-5.5-Cyber. A day of celebration for cyber defense acceleration. https://t.co/SYKQvsTA44",
      "translation": "让我们一起给整个星球打补丁。Codex 安全能力迎来更新，同时发布新的 GPT-5.5-Cyber；这是为网络防御加速庆祝的一天。",
      "avatar_url": "https://unavatar.io/x/thsottiaux",
      "url": "https://x.com/thsottiaux/status/2069152290326630518",
      "role": "builder",
      "event_date": "2026-06-22",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Aaron Levie",
      "handle": "levie",
      "editorial_category": "x_discussion",
      "content": "几乎所有 AI 模型和 agent 的进步都来自评测。面向特定领域的开源权重后训练取决于评测，应用层 agent 改进也围绕评测，真正能增强工作的企业级 agent 部署同样取决于评测。说到底都是评测。未来，理解自身或客户工作流，并衡量 agent 参与效果，将成为企业核心能力。",
      "original_text": "Almost all AI model and agent progress is downstream from evals. Open weights post training for specific domains comes down to evals. Agent improvements in the applied AI layer is all about evals. Agentic enterprise deployments that actually can augment work is all about evals. It’s all evals. This will become a core competency of any enterprise in the future. The companies that are able to best understand their own (and/or customers) workflows and how well agents participate in that work will ...",
      "translation": "几乎所有 AI 模型和 agent 的进步都来自评测。面向特定领域的开源权重后训练取决于评测，应用层 agent 改进也围绕评测，真正能增强工作的企业级 agent 部署同样取决于评测。说到底都是评测。未来，理解自身或客户工作流，并衡量 agent 参与效果，将成为企业核心能力。",
      "avatar_url": "https://unavatar.io/x/levie",
      "url": "https://x.com/levie/status/2069228335255949775",
      "role": "builder",
      "event_date": "2026-06-23",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Peter Yang",
      "handle": "petergyang",
      "editorial_category": "x_discussion",
      "content": "我读完这篇仍然不明白，Claude Code 里的 dynamic workflow 到底是什么，以及什么时候该使用它。",
      "original_text": "I'm reading this and I still don't get what a dynamic workflow is or when to use it in Claude Code https://t.co/2dlfB1Qof3 https://t.co/PESTVQfSQ1",
      "translation": "我读完这篇仍然不明白，Claude Code 里的 dynamic workflow 到底是什么，以及什么时候该使用它。",
      "avatar_url": "https://unavatar.io/x/petergyang",
      "url": "https://x.com/petergyang/status/2069267139576693028",
      "role": "builder",
      "event_date": "2026-06-23",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Swyx",
      "handle": "swyx",
      "editorial_category": "x_discussion",
      "content": "我觉得还没人真正算清楚 SpaceX 以及 NeoCloud+NeoLab 当前走向市场的账。SpaceX 已经通过算力交易收回了大约一半对 Cursor 的投资；如果 Composer 3 表现好，另一半也能覆盖。在 GPU 这个层面，没有其他公司同时是领先模型实验室和 neocloud。前提是已经充分规划 GPU 供应，无论自研训练进展非常好还是不理想，这都是非常有效的组合。",
      "original_text": "i dont think anyone is correctly doing the math around how SpaceX, the NeoCloud+NeoLab, is currently going to market? SpaceX has already recouped about HALF its investment in Cursor, in compute deals. The other half is paid for if Composer 3 does well. No other company is simultaneously a leading model lab + neocloud (at least where GPUs is concerned). its a crazy effective combo iff you've adequately planned out gpu supply if inhouse training 1) goes very well 2) doesn't go very well",
      "translation": "我觉得还没人真正算清楚 SpaceX 以及 NeoCloud+NeoLab 当前走向市场的账。SpaceX 已经通过算力交易收回了大约一半对 Cursor 的投资；如果 Composer 3 表现好，另一半也能覆盖。在 GPU 这个层面，没有其他公司同时是领先模型实验室和 neocloud。前提是已经充分规划 GPU 供应，无论自研训练进展非常好还是不理想，这都是非常有效的组合。",
      "avatar_url": "https://unavatar.io/x/swyx",
      "url": "https://x.com/swyx/status/2069301071965741388",
      "role": "builder",
      "event_date": "2026-06-23",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Peter Yang",
      "handle": "petergyang",
      "editorial_category": "x_discussion",
      "content": "我想和一位擅长用 Codex 或 Claude Code 制作有趣像素游戏、Three.js 游戏的人做一期播客，并请对方展示具体做法。我骨子里就是玩家。最应该找谁聊？",
      "original_text": "I want to do a podcast episode with someone who's good at using Codex / Claude Code to create fun pixel or threejs games and can show us how to do it. I am a gamer at heart! Who's the best person to talk to?",
      "translation": "我想和一位擅长用 Codex 或 Claude Code 制作有趣像素游戏、Three.js 游戏的人做一期播客，并请对方展示具体做法。我骨子里就是玩家。最应该找谁聊？",
      "avatar_url": "https://unavatar.io/x/petergyang",
      "url": "https://x.com/petergyang/status/2069118077313425840",
      "role": "builder",
      "event_date": "2026-06-22",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Guillermo Rauch",
      "handle": "rauchg",
      "editorial_category": "x_discussion",
      "content": "Guillermo Rauch 的原帖表示：Claude Design 可以一键接到 Vercel，并附上两个演示链接。该短帖本身只传达从 Claude Design 到 Vercel 的一键连接能力，没有展开更多产品细节。",
      "original_text": "Claude Design → Vercel, in one click https://t.co/Btq9hFk7OB https://t.co/NpgdokzpvE",
      "translation": "Guillermo Rauch 的原帖表示：Claude Design 可以一键接到 Vercel，并附上两个演示链接。该短帖本身只传达从 Claude Design 到 Vercel 的一键连接能力，没有展开更多产品细节。",
      "avatar_url": "https://unavatar.io/x/rauchg",
      "url": "https://x.com/rauchg/status/2069219190834127276",
      "role": "builder",
      "event_date": "2026-06-23",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Aaron Levie",
      "handle": "levie",
      "editorial_category": "x_discussion",
      "content": "我们听说 HTML 又变得重要了。现在你可以在 Box 上预览、编辑、管理版本，并安全共享任何基于 HTML 的内容；这很适合立即处理各种 agent 生成的内容。",
      "original_text": "We heard that HTML is a big deal again. You can now preview, edit, manage versions, and securely share any HTML based content on Box. Great for being able to work with any agent produced content immediately. https://t.co/Rgo2TO6RIg",
      "translation": "我们听说 HTML 又变得重要了。现在你可以在 Box 上预览、编辑、管理版本，并安全共享任何基于 HTML 的内容；这很适合立即处理各种 agent 生成的内容。",
      "avatar_url": "https://unavatar.io/x/levie",
      "url": "https://x.com/levie/status/2069140445205348432",
      "role": "builder",
      "event_date": "2026-06-22",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    },
    {
      "author": "Ryo Lu",
      "handle": "ryolu_",
      "editorial_category": "x_discussion",
      "content": "这是我在 Cursor Compile 的演讲，分享一些关于 AI 时代我们如何构建，以及哪些东西不会改变的思考。",
      "original_text": "here's my talk at Cursor Compile some thoughts on how we build in the age of AI and what doesn't change https://t.co/otMw3nwPkr",
      "translation": "这是我在 Cursor Compile 的演讲，分享一些关于 AI 时代我们如何构建，以及哪些东西不会改变的思考。",
      "avatar_url": "https://unavatar.io/x/ryolu_",
      "url": "https://x.com/ryolu_/status/2069218497272717661",
      "role": "builder",
      "event_date": "2026-06-23",
      "source": "follow-builders X feed",
      "importance": "notable",
      "image_urls": []
    }
  ],
  "official_org_updates": [],
  "evidence_assets": [],
  "generated_at": "2026-06-24T02:37:38.197Z",
  "report_status": "normal",
  "canonical_url": "https://jasonxzwen.github.io/ai-daily-cn/reports/2026/06/2026-06-24.html",
  "html_path": "reports/2026/06/2026-06-24.html",
  "quality_status": {
    "status": "degraded",
    "public_note": "Some discovery coverage is degraded; this report may be incomplete.",
    "affected_sections": [
      "huggingface_trending"
    ],
    "degraded_events": [
      {
        "section": "huggingface_trending",
        "message": "huggingface_trending coverage is degraded and should be disclosed in the public report.",
        "severity": "degraded"
      }
    ]
  }
}
