{ "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 } ] }