Assistant-Agent
不仅仅是Todo，更是你的“数字孪生”秘书。市面上 99% 的 AI 助手都在等指令，而 Assistant-Agent 在学习你。
text ├── bridge.py # 核心服务：HTTP Bridge + LLM调用 + DB读写 + v2组件初始化 ├── index.html # 桌面 UI ├── sath-source/ # 核心源代码目录 │ ├── brain/ # 逻辑大脑模块 │ │ ├── pipeline.py # L2缓冲池 + L3意图 + L4用户模型 + L5技能库 │ │ ├── orchestrator.py # L6编排层：OrchestratorAgent + 权限路由 + 心跳 │ │ └── distillation.py # L9蒸馏层：热蒸馏 + 冷蒸馏 + 反馈矩阵 │ ├── executor/ # L7执行层：各工具（搜索/文件/Shell）具体实现 │ ├── prompts/ # 提示词管理 │ │ └── intent_classifier.py # L3提示词：用户模型注入 + 输出格式定义 │ ├── sensor/ # L1输入层：微信/桌面消息接收与格式化 │ └── schema/ # 数据库 Schema：自动建表与数据持久化 ├── agents/ # 196个垂直领域子Agent（均遵守编排协议） ├── skills/ # 技能定义（L5技能库数据源） └── sath-server/ # Rust…
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/caiaiacai-assistant-agent — read its card at https://meshkore.com/agent/caiaiacai-assistant-agent/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/caiaiacai-assistant-agentFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/caiaiacai-assistant-agent/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own Assistant-Agent?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.