docs: add Structured Output and Task Retry to feature list

README.md

@@ -16,6 +16,8 @@ Build AI agent teams that decompose goals into tasks automatically. Define agent
 - **Multi-Agent Teams** — Define agents with different roles, tools, and even different models. They collaborate through a message bus and shared memory.
 - **Task DAG Scheduling** — Tasks have dependencies. The framework resolves them topologically — dependent tasks wait, independent tasks run in parallel.
 - **Model Agnostic** — Claude, GPT, Gemma 4, and local models (Ollama, vLLM, LM Studio) in the same team. Swap models per agent via `baseURL`.
+- **Structured Output** — Add `outputSchema` (Zod) to any agent. Output is parsed as JSON, validated, and auto-retried once on failure. Access typed results via `result.structured`.
+- **Task Retry** — Set `maxRetries` on tasks for automatic retry with exponential backoff. Failed attempts accumulate token usage for accurate billing.
 - **In-Process Execution** — No subprocess overhead. Everything runs in one Node.js process. Deploy to serverless, Docker, CI/CD.
 
 ## Quick Start

README_zh.md

@@ -16,6 +16,8 @@
 - **多智能体团队** — 定义不同角色、工具甚至不同模型的智能体。它们通过消息总线和共享内存协作。
 - **任务 DAG 调度** — 任务之间存在依赖关系。框架进行拓扑排序——有依赖的任务等待，无依赖的任务并行执行。
 - **模型无关** — Claude、GPT、Gemma 4 和本地模型（Ollama、vLLM、LM Studio）可以在同一个团队中使用。通过 `baseURL` 即可接入任何 OpenAI 兼容服务。
+- **结构化输出** — 为任意智能体添加 `outputSchema`（Zod），输出自动解析为 JSON 并校验，校验失败自动重试一次。通过 `result.structured` 获取类型化结果。
+- **任务重试** — 为任务设置 `maxRetries`，失败时自动指数退避重试。所有尝试的 token 用量累计，确保计费准确。
 - **进程内执行** — 没有子进程开销。所有内容在一个 Node.js 进程中运行。可部署到 Serverless、Docker、CI/CD。
 
 ## 快速开始