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Gemini Executive Synthesis

Bridging interactive `ask_user_question` tool calls from DeepSeek Harness to various IM channels, enabling multi-turn conversational AI with user confirmation.

Technical Positioning
Enhancing the interactive capabilities of IM bots by ensuring `ask_user_question` prompts are fully integrated into chat workflows, preventing conversational deadlocks and improving user engagement in enterprise environments.
SaaS Insight & Market Implications
This issue identifies a critical functional gap: the `ask_user_question` tool, essential for interactive AI workflows requiring user confirmation, fails to bridge to IM channels. This results in conversational deadlocks, forcing users to resort to the web UI, which is impractical and breaks the core IM bot experience. For B2B SaaS, particularly in enterprise settings like WeChat Work, this limitation severely impacts the utility of AI agents for tasks requiring human input or approval. The proposed solution—integrating interactive prompts directly into IM conversations with structured options and timeout policies—is crucial for enabling robust, multi-turn AI interactions. Without this, the platform's ability to handle complex, human-in-the-loop processes is compromised, limiting its market appeal for sophisticated enterprise automation.
Proprietary Technical Taxonomy
ask_user_question IM 渠道 确认门 永久卡死 请求转发交互问题 企微 dsh-im DSH

Raw Developer Origin & Technical Request

Source Icon GitHub Issue Aug 26, 2026
Repo: xmanrui/dsh-im
[Feature] ask_user_question 未桥接到 IM 渠道,含确认门的 skill 会永久卡死(请求转发交互问题到企微等渠道)

### 环境 / Environment

- dsh-im: `@xmanrui/dsh-im` **3.0.4**
- DSH: `0.1.0-rc.5`(源码运行)+ 官方 CLI `0.1.1-rc.2`,macOS (darwin arm64)
- 渠道:**企业微信**(官方 WebSocket 长连接,`@wecom/aibot-node-sdk`)
- 场景:机器人为一个带「执行前确认门」的自定义 skill(该 skill 按规范在数据装配前调用 `ask_user_question` 请求用户确认口径)

### 问题 / Problem

`ask_user_question` 工具调用**不会被桥接到 IM 渠道**:在 `lib/index.js` 中 grep `ask_user_question` 为 0 处。结果:

1. agent 调用 `ask_user_question` 后,企微侧**什么都收不到**(普通文字消息、流式回复都正常,唯独交互式问题没有);
2. 回合进入 `等待回答` 状态并**永久卡死**——用户根本不知道有问题是给他的;
3. 只有在 web UI 打开该会话才能看到待答问题(这是目前的逃生门),IM 用户不可能自己发现。

### 复现步骤 / Repro

1. 绑定企微机器人,工作区放一个会调用 `ask_user_question` 的 skill(或直接让 agent「用 ask_user_question 向我确认一个选项」);
2. 在企微里下达会触发确认的指令;
3. 企微收到执行预览的**文字**消息后,agent 调用 `ask_user_question` → 企微再无任何新消息;
4. 会话轨迹(`~/.dsh/sessions//session-*/session.jsonl.zstd` 解压后)可见:

```
[tool/call] {"name": "ask_user_question", "arguments": "{\"questions\":[{\"id\":\"confirm_run\",\"question\":\"以上执行方案…是否确认开始?\",\"options\":[\"确认,开始执行\",…]}]}"}
(之后再无事件 —— 回合挂起等待永远无法送达用户的答案)
```

5. web UI 会话列表显示「等待回答 · N分钟」,在 web UI 内作答后回合立即恢复。

### 期望 / Feature Request

把用户问题桥接进 IM 会话本身,例如:

- 收到挂起的 `ask_user_question` → 用渠道消息发送「问题 + 带编号的选项」(Markdown 文本即可,无需平台特殊交互组件);
- 用户在 IM 回复 `1` / 选项文字 → 映射回答案并提交,回合继续;回复不匹配时重发一次选项提示;
- 附带超时策略(如 N 分钟未答则按超时/默认选项处理,可配置);
- 对不支持多轮等待的渠道可降级为「自动选推荐项 + 文字告知」的开关。

会话映射、双向通道、流式回复这些管道 dsh-im 都已具备,这个桥接主要是复用现有管道做事件→消息→答案的回填。AI Office 人工面板已经覆盖了同类需求的事件侧,但对用户来说它离开了聊天上下文、且依赖公网 Office(企业数据流经外部服务,不少场景过不了合规)。

### 当前的临时缓解 / Workaround

- 工作区 `AGE...

Developer Debate & Comments

wangwenming-github • Aug 26, 2026
补充一个相关实证(same root area, delivery side):当回合因 `ask_user_question` 暂停、由 web UI 端作答恢复后,**同一 turn 的后续所有流式播报与最终交付消息都不再送达 IM**(用户只收到提问前的早期消息);turn 正常 `completed`。而之后用户新发一条消息开启的**新 turn 交付完全正常**(文字+文件附件均可达)。看起来转发/订阅的生命周期与提问暂停或超长回合(本例 67 分钟)存在冲突。环境同主帖:dsh-im 3.0.4 + DSH 0.1.0-rc.5,企业微信渠道。
xmanrui • Aug 26, 2026
我测试没复现你说的问题

Adjacent Repository Pain Points

Other highly discussed features and pain points extracted from xmanrui/dsh-im.

Extracted Positioning
WeChat login functionality for the `dsh-im` integration with DeepSeek Harness.
Ensuring seamless and reliable multi-channel IM bot integration, specifically for WeChat, after software updates.
Top Replies
xmanrui • Aug 27, 2026
最新版本吗?
hgl011091 • Aug 27, 2026
DSH Desktop和dsh-im都是最新版
xmanrui • Aug 27, 2026
> 微信扫码成功了,提示报错 用的是哪个版本的DeepSeek Harness?
Extracted Positioning
WeChat integration activation and error diagnosis for DeepSeek Harness.
Ensuring reliable and diagnosable WeChat integration activation by providing granular error codes and detailed logging, improving troubleshooting efficiency and user experience during bot setup.
Top Replies
xmanrui • Aug 21, 2026
你好,感谢反馈。 从 `activation-failed` 可以确认:微信扫码授权已经成功,问题发生在授权后的激活阶段。这个阶段依次包括:保存 `bot_token` 到 DSH 凭据服务、写入账号/状态/工作区配置、检查本机 Harness,...
xmanrui • Aug 21, 2026
微信激活阶段的错误分类和失败回滚已在 `@xmanrui/dsh-im@0.15.0` 中完善。 请先更新插件: ```bash dsh plugin --profile web update -L @xmanrui/dsh-im ``` 更新后请重启 `dsh web`,再重新扫码绑定。 如果仍...
Czj1997-02 • Aug 21, 2026
微信已授权,但插件无法连接本机 Harness。请确认 dsh web 已正常启动。 harness-unreachable 有没有可能是我是源码启动的原因 pnpm dsh web
Extracted Positioning
Adding Matrix channel integration to DeepSeek Harness.
Expanding DeepSeek Harness's multi-channel integration capabilities to include Matrix, catering to users and organizations that prioritize open standards, decentralized communication, and data sovereignty.
Top Replies
xmanrui • Aug 23, 2026
感谢建议!Matrix 频道确实很有价值。 不过我目前没有实际使用 Matrix 的经验,对 Homeserver、房间/邀请流程以及 E2EE 的真实使用场景还不够熟悉。为了避免只依据文档实现、却遗漏实际使用中的关键行为,想请问...
ChrisLou-bioinfo • Aug 23, 2026
非常高兴收到团队的回复,我自己也在开发im相关项目,但看到你们这个项目我觉得大部分工作已经不需要去做了。Matrix是可以私有化部署im的工具,尽管不部分im生成保护隐私,但数据流向必然决定着不是100%保险。Mat...
xzhsy2021 • Aug 25, 2026
https://github.com/zhuiyueya/dsh-im-gateway.git 有一个类似的项目已实现matrix支持 可以看下。
Extracted Positioning
Implementing DingTalk `@` mention functionality and sender information retrieval in group chats.
Enhancing DingTalk integration to support native `@` mentions for targeted notifications and enabling sender identification in group chats, thereby improving user engagement and contextual awareness for bots in enterprise communication.
Top Replies
xmanrui • Aug 24, 2026
钉钉@ 功能是指什么?
divingleee • Aug 24, 2026
在钉钉群聊的时候,用户A发送了消息给机器人,机器回复用户A时,可以 @A 用户,这样A用户钉钉就会有红点,提示用户A你有新消息了
divingleee • Aug 24, 2026
在增加一个功能,群聊的时候,用户A发送消息时,可以让机器人获取到用户A发送者的信息
Extracted Positioning
User isolation and permission management for Feishu (Lark) login.
Implementing robust user isolation and granular permission management for Feishu (Lark) integrations, ensuring secure, compliant, and multi-tenant access control within the DeepSeek Harness ecosystem.
Top Replies
xmanrui • Aug 25, 2026
> 飞书免密登陆,不同用户权限隔离 没理解,能详细说明一下吗?
yangyf520 • Aug 25, 2026
> > 飞书免密登陆,不同用户权限隔离 > > 没理解,能详细说明一下吗? 你这个插件做的很棒,飞书机器人可以很容易接入了。 每个人部署一套对非业务人员不友好。 企业一般更需要做集中部署,用户通过auth2登陆(SS...
xmanrui • Aug 29, 2026
感谢补充说明,也感谢对 dsh-im 的认可。集中部署确实可以降低非技术用户的使用门槛,但经过评估,这项能力不适合直接放在 dsh-im 中实现。 dsh-im 的职责是把各类 IM 渠道连接到现有 Harness,并处理渠道身份、...

Frequently Asked Questions

Market intelligence mapped to Bridging interactive `ask_user_question` tool calls from DeepSeek Harness to various IM channels, enabling multi-turn conversational AI with user confirmation..

How is Bridging interactive `ask_user_question` tool calls from DeepSeek Harness to various IM channels, enabling multi-turn conversational AI with user confirmation. positioned in the market?
Based on our AI analysis of the original developer request, its primary technical positioning is: Enhancing the interactive capabilities of IM bots by ensuring `ask_user_question` prompts are fully integrated into chat workflows, preventing conversational deadlocks and improving user engagement in enterprise environments.
Are engineers actively discussing Bridging interactive `ask_user_question` tool calls from DeepSeek Harness to various IM channels, enabling multi-turn conversational AI with user confirmation.?
Yes, we have tracked 2 direct responses and active debates regarding this specific topic originating from GitHub Issue.
What are the foundational technologies related to Bridging interactive `ask_user_question` tool calls from DeepSeek Harness to various IM channels, enabling multi-turn conversational AI with user confirmation.?
Our proprietary extraction maps Bridging interactive `ask_user_question` tool calls from DeepSeek Harness to various IM channels, enabling multi-turn conversational AI with user confirmation. to adjacent architectural concepts including ask_user_question, IM 渠道, 确认门, 永久卡死.

Engagement Signals

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Issue Status

Cross-Market Term Frequency

Quantifies the cross-market adoption of foundational terms like web UI and DSH by tracking occurrence frequency across active SaaS architectures and enterprise developer debates.