Univer Workspace Cli

Organization

dream-num

univer-workspace-cli

Use when installing or operating the independent Univer Workspace CLI application (`univer-workspace-cli`) for remote Workspace files, Personal or Team Spaces, task Worktrees, Sheet/Doc/Slide/Base/Board Units, Facade authoring, inspection, verification, import/export, screenshots, or review handoff. Do not use for local targets handled by `univer`.

Overview

Publisher	dream-num
Repository	`skills`
Skill name	`univer-workspace-cli`
Stars	79
Forks	7
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by dream-num on GitHub. Read the source before you install it.

Installation

Install the Univer Workspace Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/dream-num/skills/tree/main/skills/univer-workspace-cli
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.

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/dream-num/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/univer-workspace-cli .claude/skills/univer-workspace-cli

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Univer Workspace Cli 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 Univer Workspace Cli 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 Univer Workspace Cli 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.

Univer Workspace CLI

Remote authoring and inspection for Univer Workspace files. The CLI provides Space discovery, per-task Worktrees, version-matched Facade guidance, model readback, and browser review.

univer-workspace-cli is independent from univer, not a variant: it operates remote Workspace files, while univer operates local univerfiles.

Install and configure the target Workspace:

bash
npm install -g univer-workspace-cli
univer-workspace-cli config set workspace.origin https://workspace.example.com
univer-workspace-cli login --json

Relay the first login command's verification URL and code to the user, then stop. Run --complete only after the user confirms approval; do not poll while approval is pending.

bash
univer-workspace-cli login --complete --json
univer-workspace-cli doctor

Keep the CLI current

Use these commands to compare the installed CLI with the latest public release:

bash
univer-workspace-cli --version
npm view univer-workspace-cli@latest version --registry=https://registry.npmjs.org/

Complete the current Workspace task before upgrading. This CLI has no update command; install the new package version explicitly, then reload its operational Skills:

bash
npm install -g univer-workspace-cli@latest
univer-workspace-cli doctor --json
univer-workspace-cli skills get core

Start here

This file is the discovery entry, not the operational guide. Before using Workspace commands for a task, load the complete core Skill from the installed CLI:

bash
univer-workspace-cli skills get core          # remote model, workflow, evidence, and handoff
univer-workspace-cli skills get core --full   # include direct references

Runtime Skills ship with the CLI so their commands and Facade APIs match the installed version.

Core Model

Configure one Workspace origin, then authenticate against it.
A Space is the file container users browse. Its tree contains Nodes identified by nodeId; a Univer Resource attached to a Node is identified by resourceId.
A Unit is editable Sheet, Doc, Slide, Base, or Board content identified by unitId after its Resource is staged in a Worktree.
Start every new task in a new Worktree. Continue a known Worktree only for rework on that same task; there is no implicit current Worktree or Unit.
Command success is not correctness evidence. Read back the stored model and inspect rendered output when appearance matters.

Use public CLI and Facade surfaces. execute commits captured mutations as one Worktree revision, and merge remains an explicit user review decision.

Unit Skills

After core, load the Skill matching the target top-level Unit before authoring:

bash
univer-workspace-cli skills get sheet
univer-workspace-cli skills get doc
univer-workspace-cli skills get slide
univer-workspace-cli skills get base
univer-workspace-cli skills get board

Use univer-workspace-cli skills list to discover the installed set. Each Unit Skill owns its creation recipe, injected Facade root, readback guidance, and visual verification requirements. For cross-Unit composition, also load univer-workspace-cli skills get embed or univer-workspace-cli skills get cross-unit-formula after the Host and Source Unit Skills.

Task Routing

Task	Load and use
Authenticate or discover a Personal/Team Space file	core
Stage an existing file or create/import a new Unit in a task Worktree	core + target Unit
Inspect or edit Sheet values, formulas, formatting, charts, or tables	core + `sheet`
Create or refine Doc paragraphs, rich text, tables, charts, or pagination	core + `doc`
Build or review Slide pages, shapes, text, images, tables, or charts	core + `slide`
Inspect or edit Base tables, fields, records, views, or formulas	core + `base`
Build or review a Board canvas and its verified elements	core + `board`
Embed a Unit or back a Chart with another Unit	core + Host + Source + `embed`
Use Source data in a formula or formula-driven Shape	core + Host + Source + `cross-unit-formula`
Verify, screenshot, export, mark ready, or generate a review URL	core + target Unit

Why Univer Workspace CLI

Space discovery resolves remote files before they enter a Worktree.
Worktrees isolate one agent task until review, merge, or discard.
Offline api show / api find resolves exact Facade symbols for the installed SDK.
Runtime inspection and the Workspace review page verify stored and rendered results.
Import/export and screenshots use the Workspace product runtime rather than unrelated file writers.

Do not substitute local office writers or bypass the remote Worktree lifecycle. Follow the loaded core and Unit Skills for the supported path.

Diagnose

bash
univer-workspace-cli --help
univer-workspace-cli doctor
univer-workspace-cli skills list
univer-workspace-cli skills path

Use univer-workspace-cli <command> --help for exact syntax. If the CLI is unavailable, the Workspace origin is not configured, authentication is missing, or doctor reports a blocking runtime failure, stop and report the diagnostic instead of switching tools.

Frequently asked questions

What does the Univer Workspace Cli AI skill do?

Why use Univer Workspace Cli on TypingMind?

Because you install it once and use it with any model. Univer Workspace Cli 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 Univer Workspace Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dream-num/skills/tree/main/skills/univer-workspace-cli. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Univer Workspace Cli?

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 Univer Workspace Cli?

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

Is the Univer Workspace Cli AI skill free?

Yes. It is published on GitHub by dream-num 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Univer Workspace CLI

Keep the CLI current

Start here

Core Model

Unit Skills

Task Routing

Why Univer Workspace CLI

Diagnose

Frequently asked questions

Related AI Skills

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