dsh-lark

專為飛書 / Lark 設計的 DeepSeek Harness（dsh）原生頻道外掛。在即時通訊中執行 Agent、切換工作區與模型，並透過人機協作卡片在聊天裡掌控關鍵決策（提問、計畫審閱、工具審批）。

DSH 整合

原生執行環境

作者聲明

安全稽核

未稽核

最後核實

2026-09-01

授權條款

BSD-3-Clause

01它能幫你完成什麼？

Run DeepSeek Harness agents from Feishu/Lark chat
Task progress, tool calls and final answers stream into Feishu/Lark as messages and interactive cards; the active workspace and model can be switched from chat
Teams and developers who run DeepSeek Harness (dsh) and want to dispatch and supervise agents from Feishu/Lark IM
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Approve or answer agent prompts without leaving Feishu/Lark
Human-in-the-loop cards — single/multi-choice or free text answers, plan approval/edits, and allow/deny tool calls
Operators and reviewers who need to control key agent decisions (questions, plan review, tool approval) from chat
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Collaborate multiple agents in one group chat
Multiple bots added with one command, handing off turns via @ mentions, with a turn cap to prevent infinite loops
Teams that want several DeepSeek Harness agents to coordinate inside a single Feishu/Lark group
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02如何將外掛接入 DeepSeek Harness？

先決條件

DeepSeek Harness (dsh) installed — if not yet, run `npm i -g @deepseek-ai/dsh`
A Feishu (Lark) account to scan the QR code and create the bot app
Node.js runtime (the channel is distributed as an npm package)

安裝步驟

01
Install the channel globally: `npm i -g dsh-lark-channel`
$ npm i -g dsh-lark-channel
02
Start it: `dsh-lark-channel start` — a QR code appears in the terminal
03
Scan the QR code with Feishu to create the app, then DM the bot or @ it in a group

驗證整合成功

Check status with `/status` to see workspace, model, session and current permission preset
Run a task in Feishu chat and confirm the agent's execution shows up as messages/cards

復原

To stop, terminate the `dsh-lark-channel start` process (Ctrl-C); if run with `npx dsh-lark-channel@latest start`, nothing was installed globally
To remove the global package: `npm uninstall -g dsh-lark-channel`

03DSH 整合程度與能力邊界

DSH 整合原生執行環境

Native DeepSeek Harness (dsh) channel for Feishu/Lark — chat-driven agent execution; replies and approvals returned as messages and interactive cards.

Chat-driven agent execution
Natural-language tasks and DSH commands typed in Feishu/Lark chat (e.g. /status, /ws, /cd, /model)→Agent reasoning, tool calls and final answers rendered in Feishu/Lark; the active workspace and model can be switched from chat
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Human-in-the-loop approval cards
Agent questions, plan proposals and tool-call requests→Interactive cards letting you answer via single/multi-choice or text, approve/modify plans, or allow/deny tool calls
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Safe dependency build strategy
First-run dependency install of the channel→pnpm build strategy written to the profile; unapproved build scripts warned and skipped so install does not fail
writes a pnpm build strategy into the profile before installing dependencies on first runskips unapproved dependency build scripts with a warning instead of failingrecords protobufjs's print-only postinstall as skipped by name
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04適合誰？何時不該用？

適合

Teams and developers who run DeepSeek Harness (dsh) and want to dispatch and supervise agents from Feishu/Lark IM
Operators and reviewers who need to control key agent decisions (questions, plan review, tool approval) from chat
Teams that want several DeepSeek Harness agents to coordinate inside a single Feishu/Lark group

不適合

A Feishu/Lark account is required to scan the QR code and create the bot app; the channel cannot start without completing app creation via the QR scan.

05相容性、維護與安全提醒

On first run the channel writes a pnpm build strategy to the profile and skips unapproved dependency build scripts (warned, not failed); protobufjs's print-only postinstall is recorded as skipped by name, so `pnpm approve-builds` is not needed manually.
A Feishu/Lark account is required to scan the QR code and create the bot app; the channel cannot start without completing app creation via the QR scan.

2026-08-142026-08-19v0.0.7

BSD-3-Clause · actively maintained (latest release v0.0.7, 2026-08-19)

06常見問題

如何安裝 dsh-lark？

全域安裝頻道套件 `npm i -g dsh-lark-channel`，再執行 `dsh-lark-channel start`。終端機會顯示 QR Code，用飛書掃描完成應用程式建立，之後私聊機器人或在群組裡 @ 它即可。若尚未安裝 DeepSeek Harness，先執行 `npm i -g @deepseek-ai/dsh`。

需要公網伺服器或回呼網址嗎？

不需要。README 說明無需公網伺服器，也無需設定回呼網址——只要用飛書掃描 QR Code 完成應用程式建立即可。

如何在聊天裡管控 Agent 決策？

模型提問、計畫審閱和工具審批都會回到目前聊天，可用按鈕或文字作答：單選 / 多選 / 文字回答問題，批准或修改計畫，允許或拒絕工具呼叫。

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