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Dingtalk Shared

OrganizationPopular
DingTalk-Real-AI
dingtalk-shared

钉钉(DingTalk) MultiSkill 的轻量共享入口。Use when 用户泛称 DWS/钉钉操作但未明确产品、请求跨产品编排、需要 URL 类型预检或产品边界消歧。清晰的单产品操作优先使用对应 dingtalk-* 子 skill；本 skill 只提供全局执行契约和按需 reference 导航，不承载产品命令全集。

Overview

PublisherDingTalk-Real-AI
Repositorydingtalk-workspace-cli
Skill namedingtalk-shared
Stars
3.1K
Forks
242
Bundled files
14
LicenseApache-2.0
Links
Skill sourceRepository
  • 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.

  • 14 bundled files

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

  • Open source

    Published by DingTalk-Real-AI on GitHub. Read the source before you install it.

Installation

Install the Dingtalk Shared 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.
  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/DingTalk-Real-AI/dingtalk-workspace-cli.git /tmp/dingtalk-workspace-cli
mkdir -p .claude/skills
cp -r /tmp/dingtalk-workspace-cli/skills/multi/dingtalk-shared .claude/skills/dingtalk-shared
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dingtalk Shared 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 Dingtalk Shared 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 Dingtalk Shared 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.

DWS 共享执行契约

本文件只在泛称 DWS、跨产品流程、URL 预检或意图不清时作为入口。明确单产品请求直接使用对应 dingtalk-* skill；已经内嵌最小执行契约的产品根 Skill 不需要先完整读取本文件。

最小 DWS 执行契约

  • 只用 dws；结构化读取加 --format json，按真实返回判断。
  • 已知命令直调；参数/约束/安全不明查 leaf 窄 Schema。Schema 不可用才读已知 leaf Help 一次；unknown flag 用同 leaf Help 修正一次。unknown command 不查 Help：优先错误中的明确 suggestion，其次已加载 Skill/reference 中的明确兼容入口；均无则报漂移并停，禁全 Catalog。低频 reference 不默认 Help，禁 root/parent/product Help。发现后必须执行或说明阻塞。
  • 不猜命令/flag/字段/ID/账号/业务事实；ID 来自真实返回。目标零命中/多候选/类型不明先消歧；仅可选时间/展示范围用契约默认，缺必需信息即停。
  • 解析/读/写同一 profile，ID 不跨组织。多账号只用唯一 isOrgCurrent=true；否则用户指定，禁止选择第一项、最近登录或最近使用账号。
  • 不输出/记录 token、refresh token、appSecret、webhook token；已注入认证时不索要。
  • 写须符合明确意图；确认以最终 Runtime gate/Schema 为准，确认后才加 --yes。
  • 写后验证结果，不凭退出码宣称成功。退出须最终答复，区分完成、部分、阻塞、待确认、失败；保留已有数据及 complete/hasMore/stopReason/failures。
  • 时间戳按会话时区展示，必要时保留原值。
  • 认证/权限/profile/confirmation/未知错误只读 dingtalk-shared 对应 reference，禁连续猜替代命令。

国际版、海外版或 .io 区域登录必须执行 dws auth login --intl（无头环境再加 --device）；--intl 只用于登录，后续业务命令按所选 profile 自动路由。

产品或跨产品规则在最小契约之上增量加载。用户已明确产品内容意图时，意图优先于 URL 形态；多账号选择与跨组织规则读取 ../dingtalk-misc/references/profile.md。本地文件、产品边界和跨产品传递规则只在对应任务中加载，避免把全局手册放入每个单产品请求。

渐进加载

只读取当前任务需要的文件，不要一次性加载全部 shared references：

当前情况必读内容
已明确单一产品对应 ../dingtalk-*/SKILL.md；不读路由 reference
泛称 DWS、需要选择产品routing.md
跨产品、多步骤、汇总或报告workflow-routing.md
输入含用户直接提供的 alidocs /i/nodes/ URL 或来源未验证的 nodeId（即使产品意图明确）url-patterns.md；先规范化 dlink 再进入目标产品
输入含其他 alidocs、shanji 等钉钉 URL 且类型不明url-patterns.md
产品边界仍然难以判断intent-guide.md 的相关章节
认证、全局 flag 或输出格式问题global-reference.md
命令已经返回错误error-codes.md；只查错误对应章节
confirmation_required / 写操作确认confirmation.md
命令发现、Schema / --compact / --allschema-usage.md
怀疑能力不支持capability-limits.md
批量/多源采集conventions.md
固定短流程lite-catalog.md 对应章节

产品命令、脚本和字段细节位于对应产品 skill，不在 dingtalk-shared 重复维护。

本 skill 作为入口时的路由顺序

  1. 先识别明确的产品内容意图；明确意图直接选择对应产品。用户直接提供的 alidocs /i/nodes/ URL 或来源未验证的 nodeId 仍须读取 url-patterns.md：先执行节点类型 探测，extension=dlink 时将 drive info 的 result.fileId 保存为入口 ID 并传给 dws doc info，再按 linkSourceInfo.nodeId 逐跳解析目标，把最终目标 ID 交给候选 产品。当前调用链已返回真实类型的稳定 ID 可直接复用。
  2. 请求包含多个时序步骤、跨产品数据传递或汇总报告：即使 URL 已识别，也要读取 workflow-routing.md，按行动指南组合需要的产品 skill；当前发布包不包含独立 scenario skill。
  3. 请求是单产品操作但产品不明确：读取 routing.md，再显式读取目标产品 SKILL.md。
  4. doc/drive/wiki、aitable/sheet、calendar/minutes 等边界仍不清楚： 只读取 intent-guide.md 的对应章节。
  5. 仍无法判断时向用户追问，不要猜测产品或命令。

跨 skill 执行

  • 正文中的相对 Read 链接是运行时依赖；metadata.requires.skills 不会自动加载。
  • 选择目标产品后，以目标 skill 的命令、参数和风险规则为准。
  • 多步骤流程按顺序传递真实返回值；可以并行的只读采集按对应 workflow/reference 执行，写操作默认串行并逐步验证。
  • 产品 skill 已内联的清晰操作直接执行；仅在遇到该 skill 未覆盖的参数或边界时读取 更深层 reference。

错误最短路径

  1. unknown command / unknown flag：运行对应层级 --help，按公开 flag 修正后最多重试一次；命令选择不确定时读 schema-usage.md。
  2. reason=confirmation_required：按 confirmation.md 处理，不要当普通校验错误放弃或静默加 --yes。
  3. 认证或权限错误：读取 global-reference.md 与 error-codes.md 对应章节。
  4. 其他错误：优先读取 JSON 错误中的 retryable、retry_after_seconds、 next_retry_at、hint 和 actions。只有明确 retryable=true 时才按服务端节奏重试； 缺少重试语义时用 --verbose 获取诊断并停止，不连续尝试替代命令。
  5. 明确不支持的能力：说明边界，不通过其他接口绕过。

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 Dingtalk Shared AI skill do?

钉钉(DingTalk) MultiSkill 的轻量共享入口。Use when 用户泛称 DWS/钉钉操作但未明确产品、请求跨产品编排、需要 URL 类型预检或产品边界消歧。清晰的单产品操作优先使用对应 dingtalk-* 子 skill；本 skill 只提供全局执行契约和按需 reference 导航，不承载产品命令全集。

Why use Dingtalk Shared on TypingMind?

Because you install it once and use it with any model. Dingtalk Shared 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 Dingtalk Shared in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli/tree/main/skills/multi/dingtalk-shared. 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 Dingtalk Shared?

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 Dingtalk Shared?

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

Is the Dingtalk Shared AI skill free?

Yes. It is published on GitHub by DingTalk-Real-AI under the Apache-2.0 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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