本次围绕 视觉分析（analyze_image） 做了端到端补齐：独立 Vision 模型经 MCP 分析本地图片，对话上下文只保留文字摘要。单代理与多代理（主/子）在 vision.enabled 且配置了模型时统一注入图片分析提示；验证码场景在系统提示、工具参数与 VL 侧有轻量约束。P0 修复包括：上传附件仅列出路径、去掉误导性的「读取文件内容」指引；提示词按 vision.Ready() 门控；Deep/Supervisor 编排的 task/transfer 交接包补充图片路径与输出格式。P1 更新了 README 中英文、docs/VISION.md、OpenAPI（VisionConfig、analyze_image、/api/config/test-vision）。钉钉/飞书/企微机器人已复用同一 Agent 与 Vision 能力，但尚不支持用户直接发图，需自行提供服务器路径。
This update completes the vision analysis (analyze_image) flow: a separate VL model via MCP reads local images and returns text-only summaries in agent context. Single- and multi-agent prompts inject image guidance only when vision is enabled with a model; captcha use cases get light hints in prompts, tool params, and the VL call. P0 fixes: chat uploads list paths only (no “read file contents” nudge), gated vision prompts, and orchestrator handoff templates for image/captcha paths. P1 adds README (EN/ZH), docs/VISION.md, and OpenAPI (VisionConfig, analyze_image, POST /api/config/test-vision). DingTalk/Lark/WeCom bots already share the same agent and vision tools, but inbound images are not supported yet—users must supply on-server file paths.