Agent skill

Workstation

by LeoYeAI in LeoYeAI/openclaw-master-skills

Control Varie Workstation sessions (Claude Code multi-session orchestration).

MITAuto-check passedAgent Workflows

Install Workstation

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill workstation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills workstation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/coding-agent-orchestrator .claude/skills/workstation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
workstation
GitHub stars
2.2k
Token cost
~4.4k tokens
SKILL.md length
2,092 words
Files
2
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Control Varie Workstation sessions (Claude Code multi-session orchestration).

  • User wants to work on / start / resume a coding project
  • SKILL.md covers Step 0: Check Pending Prompts…, Smart Routing (Main Workflow), Commands Reference and Session Control (Escape /…, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Checking session status

What it does

Workstation is an agent skill from LeoYeAI/openclaw-master-skills. Control Varie Workstation sessions (Claude Code multi-session orchestration). Use when: (1) user wants to work on / start / resume a coding project, (2) checking session status, (3) sending commands to a session, (4) listing active sessions, (5) creating new sessions, (6) user replies to a plan approval or question notification, (7) user wants to stop/cancel/interrupt a session, (8) user wants a screenshot of a session or screen. Triggers on: work on, start, resume, sessions, workers, workstation, dispatch…

Its SKILL.md is about 4.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `_meta.json`).

It sits in Agent Workflows, covering Session handoff. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • User wants to work on / start / resume a coding project
  • Checking session status
  • Sending commands to a session
  • Listing active sessions

Example prompts

  • “/workstation”

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com
    • docs.openclaw.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Workstation loads about 4.4k tokens when it runs. Until then it costs about 170 tokens; SKILL.md has 2,092 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~170
When it runs · the whole SKILL.md, loaded when a task matches
~4.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 2,092 words, ~4,376 tokens.

Download SKILL.mdSave it as .claude/skills/workstation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
workstation
description
Control Varie Workstation sessions (Claude Code multi-session orchestration). Use when: (1) user wants to work on / start / resume a coding project, (2) checking session status, (3) sending commands to a session, (4) listing active sessions, (5) creating new sessions, (6) user replies to a plan approval or question notification, (7) user wants to stop/cancel/interrupt a session, (8) user wants a screenshot of a session or screen. Triggers on: work on, start, resume, sessions, workers, workstation, dispatch, project name, approve, reject, option, pick, yes, no, stop, cancel, interrupt, escape, kill, stuck, screenshot, show me, capture, what does it look like.
version
1.0.0
homepage
https://github.com/varie-ai/workstation

Workstation Control

Control Varie Workstation coding sessions via wctl.

Step 0: Check Pending Prompts (ALWAYS DO THIS FIRST)

Before ANY routing or session work, check if a session is waiting for user input:

bash
cat ~/.openclaw/workspace/pending-prompts.json 2>/dev/null || echo '{"prompts":[]}'

If prompts array is non-empty AND the user's message looks like a response (a number, "approve", "yes", "no", "reject", short answer, or references a project in the pending list): → This is a reply to a pending prompt. Go directly to "Responding to Session Prompts" section below.

If prompts array is empty OR user's message is clearly a new request (mentions a different project, asks to start/create something, etc.): → Continue to Smart Routing below.

Smart Routing (Main Workflow)

When the user mentions working on a project (e.g., "work on my-api", "resume frontend work", "start auth refactor"), follow this decision tree silently — do NOT ask the user unless you hit an ambiguous case:

Step 1: Check daemon + list sessions
bash
wctl list

(If daemon not running, tell user to start the Workstation app.)

Step 2: Match project

Look at the repo field in each worker. Match the user's project mention against repo names (fuzzy — "frontend" matches "my-frontend-app", "api" matches "backend-api-service").

If session exists and task context aligns (user's request fits the current taskId/workContext): → wctl dispatch <session-id> "<user's message>"

If session exists but task context doesn't align (user wants to work on something different in the same repo): → Ask: "There's already a session for {repo} working on {taskId}. Should I send this to that session, or create a fresh one?"

If no session exists for the project: → Go to Step 3.

If multiple repos match (e.g., "api" could be frontend-api or backend-api): → Ask which one.

Step 3: Auto-create session (no matching session found)
bash
wctl discover

Find the project path from the discovered list, then:

bash
wctl create <repo> <path> <task-id>

Derive task-id from the user's message (e.g., "work on auth refactor" → task-id: auth-refactor). Keep it short, lowercase, hyphenated.

After creation, confirm: "Started new session for {repo} ({task-id})."

If project not found in discover results, ask the user for the repo path.

Commands Reference

CommandUse
wctl status --humanCheck daemon alive
wctl listList sessions (JSON, for parsing)
wctl list --humanList sessions (readable, for user)
wctl dispatch <id> "<msg>"Send message to existing session
wctl dispatch-answers <id> <a1> <a2>...Send multi-question answers. Use next:N for multi-select
wctl create <repo> <path> [task]Create new session
wctl escape <id>Send Escape key (cancel prompt/menu)
wctl interrupt <id>Send Ctrl+C (stop running process)
wctl enter <id>Send Enter key (confirm/dismiss)
wctl screenshot <id>Screenshot a session (focus + capture)
wctl screenshot --screenScreenshot main display
wctl set-remote-mode on|offEnable/disable remote mode (bridge auto-focus for screenshots)
wctl discoverScan for project repos

Session Control (Escape / Interrupt)

When the user wants to stop, cancel, or interrupt a session:

User saysCommand
"stop session X", "cancel", "kill it", "abort"wctl interrupt <id> (sends Ctrl+C)
"escape", "go back", "cancel prompt", "dismiss"wctl escape <id> (sends Escape key)
"press enter", "confirm", "continue", "submit"wctl enter <id> (sends Enter key)

Strategy: If unsure, try escape first (safe — cancels UI prompts). If still stuck, use interrupt (harder — sends SIGINT).

Screenshots

To show the user what a session looks like:

bash
# 1. Capture the session
wctl screenshot <session-id>
# Returns: { "status": "ok", "imagePath": "/path/to/screenshot.png" }

# 2. Send to user using the built-in message tool

To deliver the screenshot, use your built-in message tool (not bash) with action: "send" and mediaUrl pointing to the captured image path. The message tool is session-bound — it automatically targets the channel and user you're currently chatting with. No need to specify channel or target manually.

If the message tool is unavailable, fall back to the CLI:

bash
openclaw message send --media <imagePath> --channel <channel> --target <target>

Replace <channel> and <target> with the values from the current conversation (e.g., telegram + the user's chat ID, or whatsapp + their phone number).

For full screen (e.g., to see Chrome, other apps): wctl screenshot --screen

When to use: User says "show me", "screenshot", "what does it look like", "what's happening in session X".

Always send the image via openclaw message send --media after capturing — wctl only saves the file locally.

Critical Rules

  1. dispatch for existing sessions — always. It types directly into the terminal. Never use wctl route (it may restart Claude and disrupt work).
  2. Never prepend claude to messages — just pass the user's message as-is to dispatch.
  3. Add --human when showing output to user — JSON otherwise for your own parsing.
  4. Ask when unsure — if you can't confidently match the user's message to exactly one session/project, ask to confirm. Wrong dispatches disrupt real coding work. Autonomy is good, but correctness matters more.
  5. Never guess or hallucinate — don't invent project names, session IDs, or options. Always check wctl list and pending-prompts.json for ground truth.
  6. Use "Chat about this" as fallback — if you can't confidently map the user's answer to option numbers for a multi-question prompt, use --chat-arrows 20 to select "Chat about this" and then dispatch their message as text. A stuck question modal is worse than falling back to chat.

Responding to Session Prompts

When Step 0 finds pending prompts and the user's message is a response:

Step 1: Identify the target session

The pending prompt has a project field. Use it to find the session:

bash
wctl list

Find the session whose repo matches the pending prompt's project. Use its sessionId.

If multiple prompts are pending, match the user's message to the most relevant one (by project name mention or most recent).

Step 2: Map intent to response

Plan approval (4 options):

User saysDispatch
"1", "clear context", "bypass all"wctl dispatch <id> "1"
"2", "bypass permissions", "yes bypass"wctl dispatch <id> "2"
"3", "approve", "yes", "go ahead", "lgtm", "manually approve"wctl dispatch <id> "3"
"reject", "no", feedback like "change X to Y"Two steps: wctl dispatch <id> "4" then wait 2s then wctl dispatch <id> "<their feedback>"

Default to option 3 ("yes, manually approve edits") when user says generic approval like "yes", "approve", "go ahead".

Important for option 4 (feedback/reject): This is a two-step process. First dispatch "4" to select the text input option, wait 2 seconds for the text prompt to appear, then dispatch the feedback text. Example:

bash
wctl dispatch abc123 "4"
sleep 2
wctl dispatch abc123 "don't modify the database schema"

Question — ALWAYS dispatch the OPTION NUMBER, never text:

Look up the user's answer in the pending prompt's questions array and find the matching option number. Example: if options are ["1. Night", "2. Day", "3. Morning"] and user says "night", dispatch "1" (not "night").

User saysAction
A number ("1", "2")Dispatch that number directly
A word matching an option label ("night", "dog")Find the option number and dispatch the NUMBER
Free text not matching any optionDispatch the text (for "Other" option)

Single question: Use regular dispatch: wctl dispatch <id> "2"

Multiple questions: Use dispatch-answers — it sends each answer without Enter (Claude auto-advances on single-select), then sends Enter at the end to submit. Map EACH answer to its option NUMBER, then pass them all in one command:

bash
wctl dispatch-answers <id> 2 1 3

This sends: "2" → wait → "1" → wait → "3" → wait → Enter (submit). No chaining or sleep needed — timing is handled internally.

Multi-select questions (checkboxes — check the multiSelect field in pending-prompts.json): Typing a number toggles it on/off but does NOT advance (cursor stays at position 1). After selecting all options, use next:N to arrow-down N times to the "Next"/"Submit" button and press Enter. N = the number of options for that question (including "Other"), from questions[i].options.length.

bash
wctl dispatch-answers <id> 1 2 next:5 2

This sends: "1" (toggle) → "2" (toggle) → arrow-down×5 to "Next" → Enter → "2" (next question, single-select) → Enter (submit all).

Example with 4 questions (multi/5opts, single, single, multi/5opts):

bash
wctl dispatch-answers <id> 1 4 next:5 2 1 1 3 next:5

Each next:N is self-contained — N is always questions[i].options.length for that specific multi-select question.

How to tell if a question is multi-select: The pending prompt's questions array has a multiSelect field per question. If multiSelect: true, you MUST add next:N after their selections. If multiSelect: false (or missing), it's single-select and auto-advances — no next needed.

If the last question is multi-select, use next:N as the last token — it will click "Submit" instead of "Next" (same button position). The final Enter to confirm all answers is sent automatically after all tokens.

"Chat about this" — at the very bottom of the question modal (below all options and Next/Submit), there's a "Chat about this" option. Arrow keys do NOT wrap/circulate, so you can safely overshoot. Use --chat-arrows N to select it. Calculate N based on the first question only:

  • First question is multi-select with K options (incl. Other): --chat-arrows K+1 (extra arrow for Next button)
  • First question is single-select with K options (incl. Other): --chat-arrows K
bash
# Example: first question is multi-select with 5 options → 6 arrows
wctl dispatch-answers <id> --chat-arrows 6
# Example: first question is single-select with 3 options → 3 arrows
wctl dispatch-answers <id> --chat-arrows 3

When using --chat-arrows, no answer tokens are needed — it replaces the entire answer flow.

FALLBACK RULE: If you are unsure how to map the user's answers to option numbers, or the user's message is vague/unclear, always use --chat-arrows instead of guessing. This lets the user follow up with a simple text prompt rather than getting stuck on a broken selection. Since arrows don't wrap, you can safely use --chat-arrows 20 if unsure about the exact count — it will land on "Chat about this" regardless.

After selecting "Chat about this", immediately dispatch the user's message as a follow-up:

bash
wctl dispatch-answers <id> --chat-arrows 20
sleep 3
wctl dispatch <id> "<user's original message>"
Show full SKILL.md (644 more words)Show less
Step 3: Confirm

After dispatching, tell the user: "Sent response to {project}."

Errors

  • daemon not running → tell user to start Workstation app
  • session not found → wctl list to show valid IDs
  • project not in discover → ask user for repo path
  • timeout → session busy, retry shortly

Quick Start

Install
  1. Install the Varie Workstation Electron app (macOS arm64).
  2. Install wctl (the CLI that bridges OpenClaw to Workstation):
    bash
    # wctl ships with Workstation — symlink it to your PATH:
    ln -sf /path/to/varie-workstation/openclaw/wctl.js ~/.local/bin/wctl
    chmod +x ~/.local/bin/wctl
  3. Copy this skill to your OpenClaw workspace:
    bash
    cp -r workstation ~/.openclaw/workspace/skills/workstation
Configure
  • Launch the Workstation app and verify it's running: wctl status
  • Enable remote mode for mobile screenshot support: wctl set-remote-mode on
  • The OpenClaw-Workstation bridge (bundled in the app) writes pending prompts to ~/.openclaw/workspace/pending-prompts.json — this enables bidirectional question/approval flows from your phone.
Verify
bash
wctl status --human    # Should show "Workstation is running"
wctl list --human      # Should list active sessions (if any)

Prerequisites

This skill requires the Varie Workstation app — an Electron-based multi-session Claude Code orchestration environment. The skill is the mobile control layer: it lets you manage Workstation sessions from Telegram, WhatsApp, or any OpenClaw channel.

DependencyWhat it doesRequired?
Varie WorkstationElectron app hosting Claude Code terminalsYes
wctl CLIBridges OpenClaw commands to Workstation's Unix socketYes (ships with Workstation)
OpenClaw-Workstation bridgeForwards session events (questions, approvals) to OpenClaw for mobile notificationsYes (bundled in Workstation)

Without Workstation running, the skill will report "daemon not running" for all commands.

Security & Guardrails

Permissions
  • wctl communicates with Workstation via a local Unix socket (/tmp/varie-workstation.sock). No network calls — all traffic is local.
  • Screenshot capture requires macOS Screen Recording permission for the Workstation app.
Declared File Access
  • ~/.openclaw/workspace/pending-prompts.json (read-only) — This file is read on every invocation (Step 0) to check if any Claude Code session is waiting for user input. It is written by the OpenClaw-Workstation bridge, not by this skill. Contents: question text, option labels, and project identifiers from active sessions. No credentials, secrets, or user data. The file may not exist until the bridge creates it — the skill handles this gracefully with a fallback empty response.
Screenshots
  • Session screenshots (wctl screenshot <id>) capture only the specific Workstation terminal window for the targeted session.
  • Full-screen screenshots (wctl screenshot --screen) capture the entire display, which may include unrelated windows and sensitive content. This command is only executed when the user explicitly requests a full-screen capture (e.g., "screenshot my screen", "show me everything").
  • Screenshots are saved locally to ~/.openclaw/media/ with a 30-minute TTL cleanup.
  • Screenshots are sent only to the user's own messaging channel (Telegram/WhatsApp) — never to third parties or external services.
Confirmations Before Risky Actions
  • The skill asks for confirmation before creating new sessions or when multiple repos match ambiguously.
  • wctl interrupt (Ctrl+C) is reserved for explicit user requests — the skill never sends it autonomously.
Data Handling
  • openclaw message send routes media through your configured OpenClaw channel (Telegram/WhatsApp). Images traverse the channel provider's servers but are only sent to the requesting user's conversation.
Input Validation
  • The skill maps user intent to option numbers before dispatching — free text is never injected into PTY commands without validation.
  • The "Chat about this" fallback is used whenever intent mapping is uncertain, preventing wrong selections.

External Endpoints

EndpointProtocolData Sent
/tmp/varie-workstation.sockUnix socket (local)Session commands (list, dispatch, create, screenshot)
~/.openclaw/workspace/pending-prompts.jsonLocal file readNone (read-only)
openclaw message send --channel --targetOpenClaw channel (Telegram/WhatsApp)Screenshot images (when user requests)

No external APIs are called directly by this skill. All network communication goes through OpenClaw's channel layer.

Trust Statement

This skill controls local Claude Code sessions running inside the Varie Workstation app. All communication is via local Unix socket — no data leaves your machine unless you request a screenshot, which is sent through your configured OpenClaw messaging channel. Only install if you trust the Varie Workstation app and your OpenClaw channel configuration.

Publisher

@masqueradeljb

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/coding-agent-orchestrator of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Workstation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Workstation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Workstation this skillLeoYeAI/openclaw-master-skills2.2k—~4.4kAutomated safety check: PassMIT
Orca CLIstablyai/orca88k2 repos~593Automated safety check: PassMIT
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Session History Searchslopus/happy24k—~3.1kAutomated safety check: PassMIT
Paseo Agent Handoffgetpaseo/paseo20k1 repos~606Automated safety check: PassCustom licence
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: NotesCustom licence

Similar skills

  • Orca CLI

    stablyai/orca

    Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser…

    88k GitHub starsUsed in 2 repos~593 tokens
    Agent WorkflowsAuto-check passed
  • Beads Task Memory

    gastownhall/beads

    Tracks multi-session work with dependencies in the bd issue tracker so the agent can find ready tasks and recover its context after conversation compaction.

    28k GitHub stars~1.2k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Searches past Claude Code, Codex and Cursor sessions and summarizes what was worked on, tried or decided, using extraction scripts instead of reading raw logs.

    24k GitHub stars~3.1k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Paseo Agent Handoff

    getpaseo/paseo

    Hands off the current task, including context, decisions and failed attempts, to a fresh agent through Paseo by writing a self-contained briefing prompt and launching that agent.

    20k GitHub starsUsed in 1 repo~606 tokens
    Agent WorkflowsAuto-check passed
  • Memori Long-Term Memory

    MemoriLabs/Memori

    Connects Claude Code to Memori Cloud for long-term memory, recalling stored context before substantive replies and saving new context afterward.

    17k GitHub stars~2k tokensUpdated 6 days ago
    Agent WorkflowsAuto-check: notes
  • Beads

    liwp/again

    A skill your agent uses when working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory.

    118 GitHub starsUsed in 6 repos~537 tokens
    Agent WorkflowsAuto-check passed

More from LeoYeAI/openclaw-master-skills

All 1,235 skills in this repo
  • DevOps Pipeline Management

    LeoYeAI/openclaw-master-skills

    Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.

    2.2k GitHub stars~4.2k tokensUpdated 2 mo ago
    Auto-check: notes
  • Feishu Document Collaboration

    LeoYeAI/openclaw-master-skills

    Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.

    2.2k GitHub stars~2k tokensUpdated 2 mo ago
    Auto-check passed
  • Files Memory System

    LeoYeAI/openclaw-master-skills

    Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.

    2.2k GitHub stars~3.8k tokensUpdated 2 mo ago
    Auto-check passed
  • GEO-Claw AI Visibility Agent

    LeoYeAI/openclaw-master-skills

    Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.

    2.2k GitHub stars~4.7k tokensUpdated 2 mo ago
    Auto-check passed
  • Google Workspace CLI

    LeoYeAI/openclaw-master-skills

    Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.

    2.2k GitHub stars~2.6k tokensUpdated 2 mo ago
    Auto-check: notes
  • HealthFit Health Advisors

    LeoYeAI/openclaw-master-skills

    Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.

    2.2k GitHub stars~4.4k tokensUpdated 2 mo ago
    Auto-check passed

Categories

Questions about Workstation

What does Workstation do?

Control Varie Workstation sessions (Claude Code multi-session orchestration). Workstation is an agent skill from LeoYeAI/openclaw-master-skills. Control Varie Workstation sessions (Claude Code multi-session orchestration).

When should I use Workstation?

Workstation fits situations like: user wants to work on / start / resume a coding project; checking session status; sending commands to a session; listing active sessions.

How do I install Workstation in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill workstation -a claude-code`. Or copy the skill folder (skills/coding-agent-orchestrator in LeoYeAI/openclaw-master-skills) into .claude/skills/workstation in your project. Claude Code loads it when a task matches its description.

How do I install Workstation in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill workstation -a codex`. Or copy the skill folder (skills/coding-agent-orchestrator in LeoYeAI/openclaw-master-skills) into .agents/skills/workstation in your project. Codex loads it when a task matches its description.

Can I use Workstation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill workstation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/workstation, .gemini/skills/workstation, .github/skills/workstation and .opencode/skills/workstation in your project.

What does Workstation need to run?

SKILL.md names no scripts, command-line tools or credentials: Workstation is instructions for the agent only.

Does Workstation access the network?

SKILL.md names 2 domains. As links in the text: github.com and docs.openclaw.ai. This is read from the text; nothing was executed.

Is Workstation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Workstation use?

Workstation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Workstation use?

About 4.4k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Workstation?

Skills that share tags, products or a category with Workstation: Orca CLI (stablyai/orca, 88k stars), Beads Task Memory (gastownhall/beads, 28k stars), Session History Search (slopus/happy, 24k stars) and Paseo Agent Handoff (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Workstation?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,160 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.