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dsh-plugin-teamflow

dsh-plugin-teamflow

工作流 更新于 2026.08.26

在终端中运行以下命令:

dsh plugin install MichaelShii/dsh-plugin-teamflow

将以下提示词粘贴到 DeepSeek Harness 对话框中:

在终端执行 dsh plugin install MichaelShii/dsh-plugin-teamflow(源码地址 https://github.com/MichaelShii/dsh-plugin-teamflow ),安装完成后重启 dsh --profile web 即可在模型侧与浏览器工作台生效。

插件介绍

You type a single sentence like 'build a user login page' and you want the engine underneath to behave like a real product team: writing a PRD, sketching design, laying out architecture, coding, running QA, and handing off for acceptance. TeamFlow turns DeepSeek Harness into that orchestration layer. You drop the requirement, a chain of specialized agents picks it up stage by stage, and you watch progress on a visual swim-lane diagram and a drag-and-drop backlog board instead of scrolling through raw logs.

Under the hood, TeamFlow is obsessed with preventing fake delivery. Every stage has a token circuit breaker (60k budget by default); outputs that are merely polite refusals or fall below a length floor are rejected and retried; context-exhaustion failures are flagged for human review rather than blindly replayed; two consecutive agent failures in the same stage route the work to a needs-human queue. Checkpoints are written to disk after each stage, so a crash or restart simply resumes from the first incomplete stage while reusing deliverables already produced. Backlog items—requirements, tasks, bugs—are persisted per workspace and survive restarts. A lite mode skips the standalone technical-design stage for small features, saving roughly 64% of wall-clock time and 88% of tokens in real runs.

A dedicated Team Workspace tab in the browser lets every stakeholder watch stage progress in real time, drag cards across the kanban to triage defects, and inspect per-stage token usage without reading code. The completed run automatically reports back into the main chat, summarizing status, stage statistics, cumulative token spend, and suggested next actions so the model can take over from there.

It is built for small-to-medium teams already running DeepSeek Harness in the web profile who want a single sentence to become a trackable, resumable, auditable set of engineering artifacts without juggling a pile of ad-hoc prompts. Developers get real token accounting per stage, parallel task execution with configurable concurrency, and clean exit semantics that leave no residue in AGENTS.md; product managers and QA engineers get a visual board they can actually navigate.

截图预览

使用场景

  • 一句话需求自动拆分为PRD、开发、QA、验收多阶段流水线
  • 流水线中断或崩溃后从断点续跑,已完成阶段不重复执行
  • 非开发角色通过Web看板拖拽流转需求、任务和缺陷

适合人员

  • 已使用 DeepSeek Harness Web Profile 的小到中型团队
  • 希望将自然语言需求转化为可追踪工程产物的开发者
  • 需要可视化进展与token成本的非技术干系人