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Workdsh Workbench Dev

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techflag
workdsh-workbench-dev

在官方 Creator 插件开发流程上补充 WorkDSH 业务 SDK、对象协作、身份和数据保护规范。

Overview

Publishertechflag
Repositoryworkdsh
Skill nameworkdsh-workbench-dev
Stars
262
Forks
73
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by techflag on GitHub. Read the source before you install it.

Installation

Install the Workdsh Workbench Dev AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/techflag/workdsh/tree/main/packages/plugins/skills/resources/skills/workdsh-workbench-dev
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/techflag/workdsh.git /tmp/workdsh
mkdir -p .claude/skills
cp -r /tmp/workdsh/packages/plugins/skills/resources/skills/workdsh-workbench-dev .claude/skills/workdsh-workbench-dev
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Workdsh Workbench Dev in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Workdsh Workbench Dev on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Workdsh Workbench Dev is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

工作台插件开发

先通过宿主技能工具加载官方 cordis-plugin-development,在官方 Creator(创造模式,cordis)中使用原生会话、权限与工具链。本 Skill 只补充 WorkDSH 的业务约束;Host、Client、Loader、Slots、插件包和安装流程遵循官方 Skill,不另造开发 Agent、会话界面或安装器。

再阅读 需求定义 和 工作台产品体验,从一句想法开始时先阅读 需求梳理,首次制作阅读 首次开发,修改已有插件阅读 继续调整。用户本轮的范围、布局选择和暂停要求优先;这些文档不代表能力已经实现。

共同规则

  1. 从“和 AI 一起梳理”进入且尚未确认需求时,先调用 workbench_read_creation_request,阅读 需求梳理,帮助用户明确目标并保存可编辑摘要,不生成源码、构建或安装。用户在左侧确认后,当前会话会关联正式需求与开发工程;已进入开发时先调用 workbench_read_development_context,读取当前原生会话实际关联的需求、源码、稳定插件身份、目标实例和候选包;不根据旧提示词猜测归属。先使用上下文 sdk 提供的已解析公开文档与类型;不要用 Service.listService 查询已知未收录的 WorkDSH 注册服务。官方 API 按官方 Skill 核对本轮用到的服务、事件、工具和 Slot,避免枚举无关接口。WorkDSH 扩展接口须按 SDK 核验 单独核对:官方 Service 目录未收录不等于服务未运行,Config 的 absent 不等于插件未安装。WorkDSH 业务 SDK 和模板也以宿主实际交付的版本为准。不得猜测接口、复制私有实现或伪造回执;缺能力时保留源码和具体未完成项。
  2. 先定义业务对象、状态、用户动作、AI 分工和成果落点,再安排模块。项目关联是可选的;项目、资料、技能、专家、连接器使用各自公开服务和授权,不复制管理系统。一个包只声明一个工作台,后续保持包名与工作台 ID;本地制作不要求公开 GitHub 仓库。
  3. 保持用户已选布局,包括业务在左、原生会话在右的并排方式;不因套用模板强制重构。复用完整原生会话及其执行过程,不自制 Composer、聊天进度或工具轨迹。AI 通过真实业务工具读取当前对象、执行并写回候选或独立草稿,页面读取后供用户继续加工或采用;跳转聊天、复制提示词或回复结束都不等于完成业务协作。
  4. Excel、CSV 等文件复用系统 Office 的公开预览、编辑、保存和导出能力,不另写电子表格编辑器。业务页面负责字段对应、核对和统计;资料引用准确的资产及版本,统计由代码对完整已授权输入的固定修订确定性计算,不能拿截断预览作统计源。保存新文件版本后明确采用,历史分析与报告保留原快照。
  5. 对象、输入版本、会话和身份必须匹配;切换对象、账号或迭代后,旧回复不能写入新对象。保持现有源码、会话历史、用户草稿和业务数据,交接不能覆盖未发送的输入。企业请求只走 Host 已授权业务服务,不向页面提供通用带凭据代理;token、密码和密钥不进入页面、提示词、源码、日志、导出或插件包。
  6. 工作台默认按可持续使用的软件交付:围绕业务记录组织首页、列表、详情与返回路径,复杂任务使用应用内导航或页签,不把全部功能纵向堆成无限长页;多记录和页面数量根据本轮业务决定,用户明确要求的一次性工具除外。具体执行 软件形态要求。页面使用中文业务字段,说明当前任务、结果与下一步,呈现正常、异常、空数据和失败恢复状态。业务插件不自行增加宿主一级菜单;平台统一通过原生“工作台”入口提供已安装应用及开发记录,不生成平级菜单。只使用实际已声明的官方公开插槽;不修改官方侧栏包、注入私有 DOM 或用缩进伪造菜单分组。平台提供的返回工作台和常用应用设置不在业务页重复实现;业务内部仍需提供返回模块或记录列表的路径,不能用浏览器返回代替。具体记录直达需要稳定对象标识和访问核对,不能拿会话链接冒充。局部修改沿用同一源码和插件身份。
  7. 通用安装使用官方 plugin_manager install_bundle,以已核实 tgz 绝对路径、enabled:false 安装;再用候选 version、sha256 调用 workbench_verify_native_installation 核对字节并登记。activationVerified:false 只表示本工具未核验启用,绝不表示停用或启用失败,不因此重复安装。用户已授权启用或打开试用时,按回执 list_bundles(沿 nextOffset 分页)找到实际包名并核对版本、error,再 set_bundle,target 为该包名、enabled 为 true;读取 application、warnings、nextStep。不能猜 entryId、拼 include: 前缀或用 set_plugin 代替 bundle 选择;不能手改 Profile。不具备启用授权时,由用户在工作台列表启用。安装结果未知先核对事实;restart-required 如实报告,不自行重启其他任务。安装、登记、活动版本和页面可用分别报告。
  8. 依据用户本轮授权推进。要求先讨论时先明确工作路径;要求看效果时提供可交互效果并说明模拟范围;暂停打包时不自动构建或安装。生成代码、包检查通过、安装成功和页面可用分别报告;构建与 Slot 注册不能代替真实服务和用户操作验收。

页面验收在当前已认证的宿主应用页面操作工作台:Desktop 使用正在运行的 WebView;Web 使用当前已登录应用页面。独立任务浏览器不自动共享宿主登录态,其 401 不能证明工作台失败。此时停止独立浏览器验收路径,返回已认证宿主页面或保留“页面未验收”,不得查找、读取或复制 token、cookie、凭据文件,或添加认证请求头绕过访问控制。源码和静态检查仍可继续,但不能冒充宿主页面操作。

每轮交付

保存需求修订、源码关联和修订、当前迭代、候选版本及摘要、目标安装实例、官方安装与平台登记的实际结果、业务验收和未完成项。候选包存在、安装字节匹配不证明它由当前源码修订生成,构建来源仍需实际证据。源码和需求文件提供恢复上下文;事实以当前运行时及持久记录为准。中断后先核对结果,不自动重复安装或创建会话。

安装前的原生加载核对

Host 入口必须在 inject 中声明实际使用的每项宿主服务,包括通过 ctx.get(...) 和 ctx.storageDomain 等属性取得的服务;例如工作台注册、存储、连接与身份服务。不能只声明工作台注册服务。服务可选时使用官方可选生命周期注入,不用未声明的读取绕过依赖检查。

构建和 tgz 校验不证明插件可以启动。候选交付前,在隔离存储中通过官方 Cordis 插件生命周期加载 Host 入口,确认业务路由已注册、存储可打开、卸载可释放。直接调用 apply(ctx) 或仅导入模块不能代替这项检查,因为它们可能绕过官方注入约束。安装后分别检查真实字节、启用选择、Host 注册和 Client 页面;某组件失败时保留候选和数据,修正开发源码并增加版本号,再经正常更新流程验收,不修改已安装包文件。

交付前执行 构建后的启动检查,不要把打包成功视为应用启动成功。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Workdsh Workbench Dev AI skill do?

在官方 Creator 插件开发流程上补充 WorkDSH 业务 SDK、对象协作、身份和数据保护规范。

Why use Workdsh Workbench Dev on TypingMind?

Because you install it once and use it with any model. Workdsh Workbench Dev is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Workdsh Workbench Dev in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/techflag/workdsh/tree/main/packages/plugins/skills/resources/skills/workdsh-workbench-dev. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Workdsh Workbench Dev?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Workdsh Workbench Dev?

As many as you like. As long as a model supports skills, you can use Workdsh Workbench Dev with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Workdsh Workbench Dev AI skill free?

Yes. It is published on GitHub by techflag under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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