awoooi/docs/operations/ai-technology-radar-readback.snapshot.json

{
  "blocked_gates": [
    "sdk_installation_approved=false",
    "paid_api_calls_approved=false",
    "production_routing_approved=false",
    "telegram_send_approved=false",
    "model_provider_switch_approved=false",
    "host_write_approved=false",
    "openclaw_replacement_approved=false",
    "replay_shadow_canary_gate_required=true",
    "cost_and_data_boundary_review_required=true"
  ],
  "generated_at": "2026-06-26T03:43:13.171222+00:00",
  "high_priority_review_queue": [
    {
      "display_name": "Model Context Protocol SDK",
      "evaluation_priority": "p0",
      "gate_status": "scorecard_required_before_integration",
      "next_gate": "刷新 scorecard，若涉及 SDK/API/route/Telegram/host write 則送人工審核。",
      "requires_cost_approval": false,
      "requires_dependency_approval": true,
      "requires_security_review": true,
      "technology_area": "mcp_and_a2a",
      "technology_id": "modelcontextprotocol_sdk"
    },
    {
      "display_name": "Agent2Agent Protocol",
      "evaluation_priority": "p1",
      "gate_status": "scorecard_required_before_integration",
      "next_gate": "刷新 scorecard，若涉及 SDK/API/route/Telegram/host write 則送人工審核。",
      "requires_cost_approval": false,
      "requires_dependency_approval": true,
      "requires_security_review": true,
      "technology_area": "mcp_and_a2a",
      "technology_id": "a2a_protocol"
    },
    {
      "display_name": "Anthropic Claude Platform",
      "evaluation_priority": "p0",
      "gate_status": "scorecard_required_before_integration",
      "next_gate": "刷新 scorecard，若涉及 SDK/API/route/Telegram/host write 則送人工審核。",
      "requires_cost_approval": true,
      "requires_dependency_approval": false,
      "requires_security_review": true,
      "technology_area": "model_providers",
      "technology_id": "anthropic_claude_platform"
    },
    {
      "display_name": "Langfuse",
      "evaluation_priority": "p1",
      "gate_status": "scorecard_required_before_integration",
      "next_gate": "刷新 scorecard，若涉及 SDK/API/route/Telegram/host write 則送人工審核。",
      "requires_cost_approval": true,
      "requires_dependency_approval": true,
      "requires_security_review": true,
      "technology_area": "evaluation_and_observability",
      "technology_id": "langfuse_observability"
    }
  ],
  "integration_candidates": [
    {
      "awoooi_role": "協調者、handoff、tool tracing、guardrail 候選",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "OpenAI Agents SDK",
      "integration_surface": "agent_handoff_tracing_guardrails",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "agent_frameworks",
      "technology_id": "openai_agents_sdk"
    },
    {
      "awoooi_role": "NemoTron replay / evaluator / synthetic data gate",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "NVIDIA Nemotron + NeMo Agent Toolkit",
      "integration_surface": "offline_replay_evaluator_smoke_gate",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "agent_frameworks",
      "technology_id": "nvidia_nemotron_nemo"
    },
    {
      "awoooi_role": "事件處理與可恢復 workflow kernel 候選",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "LangGraph",
      "integration_surface": "durable_workflow_human_in_loop",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "agent_frameworks",
      "technology_id": "langgraph_runtime"
    },
    {
      "awoooi_role": "Gemini/Vertex agent stack watch-only 候選",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "Google Agent Development Kit",
      "integration_surface": "gemini_enterprise_agent_stack",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "agent_frameworks",
      "technology_id": "google_adk_stack"
    },
    {
      "awoooi_role": "MCP/A2A enterprise workflow watch-only 候選",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "Microsoft Agent Framework",
      "integration_surface": "enterprise_mcp_a2a_workflow",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "agent_frameworks",
      "technology_id": "microsoft_agent_framework"
    },
    {
      "awoooi_role": "快速 prototype / non-production 評估候選",
      "changed": true,
      "decision": "changed_requires_replay_readiness_review",
      "display_name": "CrewAI Flows + Crews",
      "integration_surface": "multi_agent_prototype",
      "recommended_actions": [
        "refresh_ai_technology_scorecard",
        "classify_business_applicability",
        "prepare_no_install_integration_note",
        "route_high_risk_items_to_human_review"
      ],
      "technology_area": "agent_frameworks",
      "technology_id": "crewai_flows"
    },
    {
      "awoooi_role": "read-only tool registry / MCP adapter 候選",
      "changed": true,
      "decision": "changed_requires_replay_readiness_review",
      "display_name": "Model Context Protocol SDK",
      "integration_surface": "tool_registry_interoperability",
      "recommended_actions": [
        "refresh_ai_technology_scorecard",
        "classify_business_applicability",
        "prepare_no_install_integration_note",
        "route_high_risk_items_to_human_review"
      ],
      "technology_area": "mcp_and_a2a",
      "technology_id": "modelcontextprotocol_sdk"
    },
    {
      "awoooi_role": "跨 Agent 溝通協定 watch-only 候選",
      "changed": true,
      "decision": "changed_requires_replay_readiness_review",
      "display_name": "Agent2Agent Protocol",
      "integration_surface": "agent_to_agent_interop",
      "recommended_actions": [
        "refresh_ai_technology_scorecard",
        "classify_business_applicability",
        "prepare_no_install_integration_note",
        "route_high_risk_items_to_human_review"
      ],
      "technology_area": "mcp_and_a2a",
      "technology_id": "a2a_protocol"
    },
    {
      "awoooi_role": "Agent / LLM / MCP trace 欄位標準與日週月報可觀測基礎",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "OpenTelemetry GenAI Semantic Conventions",
      "integration_surface": "agent_llm_trace_semantic_conventions",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "evaluation_and_observability",
      "technology_id": "opentelemetry_genai_semconv"
    },
    {
      "awoooi_role": "模型能力、成本與 routing scorecard 來源",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "OpenAI Model Platform",
      "integration_surface": "model_capability_cost_routing",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "model_providers",
      "technology_id": "openai_model_platform"
    },
    {
      "awoooi_role": "Claude model / coding agent / remediation watch source",
      "changed": true,
      "decision": "changed_requires_replay_readiness_review",
      "display_name": "Anthropic Claude Platform",
      "integration_surface": "model_capability_cost_routing",
      "recommended_actions": [
        "refresh_ai_technology_scorecard",
        "classify_business_applicability",
        "prepare_no_install_integration_note",
        "route_high_risk_items_to_human_review"
      ],
      "technology_area": "model_providers",
      "technology_id": "anthropic_claude_platform"
    },
    {
      "awoooi_role": "Gemini model capability / cost watch source",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "Google Gemini Platform",
      "integration_surface": "model_capability_cost_routing",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "model_providers",
      "technology_id": "google_gemini_platform"
    },
    {
      "awoooi_role": "RAG ingestion / indexing / connector watch source",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "LlamaIndex",
      "integration_surface": "rag_indexing_connectors",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "rag_and_vector",
      "technology_id": "llamaindex_rag"
    },
    {
      "awoooi_role": "LLM app integration connector watch source",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "LangChain",
      "integration_surface": "llm_app_runtime_connectors",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "rag_and_vector",
      "technology_id": "langchain_runtime"
    },
    {
      "awoooi_role": "現有 Postgres/pgvector 能力與版本 freshness 來源",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "pgvector",
      "integration_surface": "postgres_vector_index",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "rag_and_vector",
      "technology_id": "pgvector_vector_store"
    },
    {
      "awoooi_role": "專用 vector DB 候選，只能 sandbox 評估",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "Qdrant",
      "integration_surface": "dedicated_vector_database",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "rag_and_vector",
      "technology_id": "qdrant_vector_store"
    },
    {
      "awoooi_role": "本機 / sandbox vector store 候選",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "ChromaDB",
      "integration_surface": "local_vector_database",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "rag_and_vector",
      "technology_id": "chromadb_vector_store"
    },
    {
      "awoooi_role": "RAG / LLM app evaluation metrics 候選",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "Ragas",
      "integration_surface": "rag_eval_metrics",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "evaluation_and_observability",
      "technology_id": "ragas_eval"
    },
    {
      "awoooi_role": "LLM trace / prompt / eval observability 候選",
      "changed": true,
      "decision": "changed_requires_replay_readiness_review",
      "display_name": "Langfuse",
      "integration_surface": "llm_observability_tracing",
      "recommended_actions": [
        "refresh_ai_technology_scorecard",
        "classify_business_applicability",
        "prepare_no_install_integration_note",
        "route_high_risk_items_to_human_review"
      ],
      "technology_area": "evaluation_and_observability",
      "technology_id": "langfuse_observability"
    },
    {
      "awoooi_role": "自託管模型 serving 能力與版本 freshness 來源",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "Hugging Face Text Generation Inference",
      "integration_surface": "self_hosted_model_serving",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "model_serving",
      "technology_id": "huggingface_tgi"
    },
    {
      "awoooi_role": "自託管 LLM inference 候選，需 GPU/成本/安全 gate",
      "changed": false,
      "decision": "watch_only_no_change",
      "display_name": "vLLM",
      "integration_surface": "self_hosted_llm_inference",
      "recommended_actions": [
        "keep_watch_only_status"
      ],
      "technology_area": "model_serving",
      "technology_id": "vllm_serving"
    }
  ],
  "policy": {
    "host_write_approved": false,
    "model_provider_switch_approved": false,
    "openclaw_replacement_approved": false,
    "paid_api_calls_approved": false,
    "production_routing_approved": false,
    "raw_chat_history_synced": false,
    "read_only": true,
    "sdk_installation_approved": false,
    "telegram_send_approved": false
  },
  "primary_source_alignment": [
    {
      "agent_assignment": "OpenClaw 負責 policy guard；MarketRadar 追版本；Hermes 產審核包。",
      "awoooi_gate": "sandbox_orchestration_no_write",
      "practice": "OpenAI Agents SDK：專家協作、tool execution、approvals、state 由產品掌控",
      "source": "https://developers.openai.com/api/docs/guides/agents"
    },
    {
      "agent_assignment": "NemoTron 只做離線 replay / evaluator / smoke gate，不接 production routing。",
      "awoooi_gate": "nemotron_replay_evaluator_only",
      "practice": "NVIDIA Nemotron 3 Ultra / NeMo：長任務 Agent、profiling、evaluation、MCP / A2A 互通",
      "source": "https://developer.nvidia.com/blog/nvidia-nemotron-3-ultra-powers-faster-more-efficient-reasoning-for-long-running-agents/"
    },
    {
      "agent_assignment": "OpenClaw 仲裁狀態轉移；Hermes 記錄 replay 證據與交接原因。",
      "awoooi_gate": "incident_workflow_kernel_replay_first",
      "practice": "LangGraph：durable execution、human-in-the-loop、stateful workflow runtime",
      "source": "https://docs.langchain.com/oss/python/langgraph/overview"
    },
    {
      "agent_assignment": "MarketRadar 監控 SDK / spec；Critic 檢查資料權限與 tool safety。",
      "awoooi_gate": "read_only_tool_registry_before_write_adapter",
      "practice": "MCP：標準化 agent-to-tool / resource / prompt 連接，且需明確 user consent",
      "source": "https://modelcontextprotocol.io/specification/2025-06-18"
    },
    {
      "agent_assignment": "OpenClaw 設定協作邊界；Hermes 彙整 handoff 記錄；NemoTron 比對輸出。",
      "awoooi_gate": "agent_to_agent_interop_watch_only",
      "practice": "A2A：跨框架 Agent 溝通、委派與互通；MCP 處理工具、A2A 處理 Agent 對 Agent",
      "source": "https://a2a-protocol.org/latest/"
    },
    {
      "agent_assignment": "Critic 定義稽核欄位；MarketRadar 追語意規範版本；Hermes 產日週月報。",
      "awoooi_gate": "trace_semconv_mapping_before_runtime_export",
      "practice": "OpenTelemetry GenAI：Agent / LLM / MCP trace 語意慣例，支援可觀測與稽核",
      "source": "https://opentelemetry.io/docs/specs/semconv/registry/attributes/gen-ai/"
    }
  ],
  "priority_workplan": [
    {
      "automation_mode": "agent_auto_read_only",
      "done_definition": "API、snapshot、Markdown、schema、測試與 production readback 都能顯示技術領域、來源與 Gate。",
      "order": 1,
      "priority": "P0",
      "work_item": "AI 技術雷達 primary source 監控產品化"
    },
    {
      "automation_mode": "agent_auto_schedule_read_only",
      "done_definition": "每 6 小時可跑 watch；失敗來源會進日報，不會自動整合。",
      "order": 2,
      "priority": "P0",
      "work_item": "近即時版本 / release / docs 變更偵測"
    },
    {
      "automation_mode": "agent_auto_read_model_human_review_for_write",
      "done_definition": "每個 Agent 的角色、輸出、學習寫回與限制都能被前端讀回。",
      "order": 3,
      "priority": "P0",
      "work_item": "OpenClaw / Hermes / NemoTron / MarketRadar 專業分工與成長紀錄"
    },
    {
      "automation_mode": "agent_propose_owner_review",
      "done_definition": "高優先級變更先進 scorecard，再進 no-cost/no-write sandbox 或 replay 計畫。",
      "order": 4,
      "priority": "P1",
      "work_item": "AI 技術 scorecard 與 sandbox / replay 優先級"
    },
    {
      "automation_mode": "blocked_until_telegram_send_gate",
      "done_definition": "低中風險只告警回報；高風險需 owner approval 後才可發送或執行。",
      "order": 5,
      "priority": "P1",
      "work_item": "Telegram Bot 報告與高風險審核橋接"
    },
    {
      "automation_mode": "agent_auto_discover_human_classify",
      "done_definition": "GitHub topic / package registry / 官方 blog 可提出候選，但加入正式 watchlist 前需審核。",
      "order": 6,
      "priority": "P2",
      "work_item": "新 AI 技術探索與 watchlist 擴充"
    }
  ],
  "professional_agent_roles": [
    {
      "agent": "OpenClaw",
      "auto_scope": "維持現有 production baseline、讀取 replay / shadow 評分、拒絕無證據替換",
      "professional_role": "生產決策仲裁者、風險分級與最後 policy guard",
      "review_boundary": "任何取代、降級、生產路由切換都必須通過 replay / shadow / canary 與人工批准。"
    },
    {
      "agent": "NemoTron",
      "auto_scope": "只讀 request pack、比對候選輸出、產生 replay scorecard 草稿",
      "professional_role": "離線回放評估者、模型能力比較、合約輸出 smoke gate",
      "review_boundary": "不得自行呼叫外部 NIM/API、不得讀 labels 作答、不得進生產路由。"
    },
    {
      "agent": "Hermes",
      "auto_scope": "整理 primary source 摘要、建立 no-send 日週月報、準備人審包",
      "professional_role": "知識管理、RAG 整理、報告草稿與長期技能庫維護",
      "review_boundary": "不得同步 raw chat history、不得保存 secret、不得直接發 Telegram live report。"
    },
    {
      "agent": "MarketRadar",
      "auto_scope": "每 6 小時只讀 primary sources、產生 freshness / review queue",
      "professional_role": "AI 技術市場雷達、版本監控、來源失敗偵測",
      "review_boundary": "不得自動新增 SDK、不得自動修改 provider route 或 workflow 行為。"
    },
    {
      "agent": "Critic / Reviewer",
      "auto_scope": "檢查政策旗標、來源可靠性、成本與資安風險",
      "professional_role": "獨立審核、反例檢查、整合風險評分",
      "review_boundary": "只能輸出 blocked / candidate / owner_review，不得直接執行寫入。"
    }
  ],
  "report_contract": {
    "agent_auto_allowed_for": [
      "官方來源只讀監控",
      "版本與文件 hash 比對",
      "審核佇列分類",
      "繁中 no-send 報告草稿",
      "離線 replay fixture 準備",
      "低風險文件與讀回 snapshot 更新提案"
    ],
    "api_endpoint": "/api/v1/agents/ai-technology-radar-readback",
    "daily": "每日彙整變更、來源失敗、審核佇列與可自動處理項目。",
    "frontend_target": "/zh-TW/governance?tab=agent-market",
    "human_review_required_for": [
      "新 SDK / package / MCP server 安裝",
      "付費 API 或 token 上限變更",
      "模型 provider / 生產路由切換",
      "Telegram Bot 即時發送或審批按鈕策略變更",
      "主機、K8s、workflow、Nginx、secret 或資料層寫入",
      "OpenClaw 生產決策核心替換、拆分或降級"
    ],
    "monthly": "每月進行策略 review，決定納入 roadmap、維持 watch-only 或移出監控。",
    "near_real_time": "每 6 小時讀取 primary sources，偵測主流 AI 技術版本、文件與 release 變更。",
    "schedule_cron_utc": "0 */6 * * *",
    "schedule_enabled": true,
    "schedule_workflow": ".gitea/workflows/ai-technology-watch.yaml",
    "weekly": "每週做技術 scorecard，決定 sandbox / replay / adapter design 優先級。"
  },
  "rolling_update_controls": [
    {
      "agent_auto_action": "讀取官方文件、PyPI、npm、GitHub release、primary source hash。",
      "cadence": "每 6 小時",
      "cadence_source": "每 6 小時執行一次只讀 primary-source 檢查，偵測主流 AI 技術版本、文件與 release 變更。",
      "gate": "read_only_only",
      "output": "AI 技術 watch report、來源失敗清單、review queue。"
    },
    {
      "agent_auto_action": "依 business applicability、成本、依賴、資安、AWOOOI fit 分類。",
      "cadence": "每日",
      "cadence_source": "每日彙整變更技術，依商業適用性、依賴風險、成本風險與資安風險分組。",
      "gate": "no_send_report_until_delivery_gate",
      "output": "日報摘要與中低風險自動處理建議。"
    },
    {
      "agent_auto_action": "刷新 scorecard，決定 sandbox / replay / adapter design 優先級。",
      "cadence": "每週",
      "cadence_source": "每週刷新技術 scorecard，判斷是否值得進入 sandbox、offline replay 或 adapter design。",
      "gate": "scorecard_required_before_replay",
      "output": "週報、優先序、候選整合審查包。"
    },
    {
      "agent_auto_action": "彙整趨勢，提出 roadmap / watch-only / retire 建議。",
      "cadence": "每月",
      "cadence_source": "每月策略檢討，決定技術應納入 roadmap、維持 watch-only 或從監控清單移除。",
      "gate": "human_review_for_strategy_or_production_change",
      "output": "月報與策略審核包。"
    }
  ],
  "schema_version": "ai_technology_radar_readback_v1",
  "source_scope": {
    "agent_market_radar_readback": "docs/operations/ai-agent-market-radar-readback.snapshot.json",
    "gitea_main_evidence_basis_commit": "61cf5024",
    "scope_note": "本讀回只整合已提交的只讀來源監控、AI Agent 市場雷達與治理 gate；不包含 raw chat history、secret、session 或本機工作視窗內容。",
    "technology_source_registry": "docs/ai/ai-technology-watch-sources.v1.json",
    "technology_watch_report": "docs/evaluations/ai_technology_watch_report_2026-06-25.json"
  },
  "summary": {
    "ai_technology_radar_completion_percent": 100.0,
    "changed_technologies": 5,
    "high_priority_count": 15,
    "overall_completion_percent": 42.2,
    "review_queue_count": 5,
    "rolling_update_status": "near_real_time_watch_ready_integration_gated",
    "source_count": 52,
    "source_failures": 0,
    "technology_area_count": 6,
    "technology_count": 21
  },
  "technology_area_counts": {
    "agent_frameworks": 6,
    "evaluation_and_observability": 3,
    "mcp_and_a2a": 2,
    "model_providers": 3,
    "model_serving": 2,
    "rag_and_vector": 5
  },
  "technology_domains": [
    {
      "changed_count": 1,
      "high_priority_count": 5,
      "representative_technologies": [
        "OpenAI Agents SDK",
        "NVIDIA Nemotron + NeMo Agent Toolkit",
        "LangGraph",
        "Google Agent Development Kit"
      ],
      "technology_area": "agent_frameworks",
      "technology_count": 6
    },
    {
      "changed_count": 1,
      "high_priority_count": 3,
      "representative_technologies": [
        "OpenTelemetry GenAI Semantic Conventions",
        "Ragas",
        "Langfuse"
      ],
      "technology_area": "evaluation_and_observability",
      "technology_count": 3
    },
    {
      "changed_count": 2,
      "high_priority_count": 2,
      "representative_technologies": [
        "Model Context Protocol SDK",
        "Agent2Agent Protocol"
      ],
      "technology_area": "mcp_and_a2a",
      "technology_count": 2
    },
    {
      "changed_count": 1,
      "high_priority_count": 3,
      "representative_technologies": [
        "OpenAI Model Platform",
        "Anthropic Claude Platform",
        "Google Gemini Platform"
      ],
      "technology_area": "model_providers",
      "technology_count": 3
    },
    {
      "changed_count": 0,
      "high_priority_count": 0,
      "representative_technologies": [
        "Hugging Face Text Generation Inference",
        "vLLM"
      ],
      "technology_area": "model_serving",
      "technology_count": 2
    },
    {
      "changed_count": 0,
      "high_priority_count": 2,
      "representative_technologies": [
        "LlamaIndex",
        "LangChain",
        "pgvector",
        "Qdrant"
      ],
      "technology_area": "rag_and_vector",
      "technology_count": 5
    }
  ]
}