Back to Skills

peekaboo

steipete
Updated Today
374 views
468
45
468
View on GitHub
Designautomationdesign

About

Peekaboo is a macOS UI automation CLI that enables developers to capture screens, inspect and target UI elements, and simulate user input. It's useful for scripting UI interactions, testing, and automating workflows on macOS. Key features include a shared snapshot cache and JSON output for integration with other tools.

Quick Install

Claude Code

Recommended
Plugin CommandRecommended
/plugin add https://github.com/steipete/clawdis
Git CloneAlternative
git clone https://github.com/steipete/clawdis.git ~/.claude/skills/peekaboo

Copy and paste this command in Claude Code to install this skill

Documentation

Peekaboo

Peekaboo is a full macOS UI automation CLI: capture/inspect screens, target UI elements, drive input, and manage apps/windows/menus. Commands share a snapshot cache and most support --json-output for scripting. Run peekaboo or peekaboo <cmd> --help for flags; peekaboo --version prints build metadata. Tip: run via polter peekaboo to ensure fresh builds.

Features (all CLI capabilities, excluding agent/MCP)

Core

  • bridge: inspect Peekaboo Bridge host connectivity
  • capture: live capture or video ingest + frame extraction
  • clean: prune snapshot cache and temp files
  • config: init/show/edit/validate, providers, models, credentials
  • image: capture screenshots (screen/window/menu bar regions)
  • learn: print the full agent guide + tool catalog
  • list: apps, windows, screens, menubar, permissions
  • permissions: check Screen Recording/Accessibility status
  • run: execute .peekaboo.json scripts
  • sleep: pause execution for a duration
  • tools: list available tools with filtering/display options

Interaction

  • click: target by ID/query/coords with smart waits
  • drag: drag & drop across elements/coords/Dock
  • hotkey: modifier combos like cmd,shift,t
  • move: cursor positioning with optional smoothing
  • paste: set clipboard → paste → restore
  • press: special-key sequences with repeats
  • scroll: directional scrolling (targeted + smooth)
  • swipe: gesture-style drags between targets
  • type: text + control keys (--clear, delays)

System

  • app: launch/quit/relaunch/hide/unhide/switch/list apps
  • clipboard: read/write clipboard (text/images/files)
  • dialog: click/input/file/dismiss/list system dialogs
  • dock: launch/right-click/hide/show/list Dock items
  • menu: click/list application menus + menu extras
  • menubar: list/click status bar items
  • open: enhanced open with app targeting + JSON payloads
  • space: list/switch/move-window (Spaces)
  • visualizer: exercise Peekaboo visual feedback animations
  • window: close/minimize/maximize/move/resize/focus/list

Vision

  • see: annotated UI maps, snapshot IDs, optional analysis

Global runtime flags

  • --json/-j, --verbose/-v, --log-level <level>
  • --no-remote, --bridge-socket <path>

Notes

  • Requires Screen Recording + Accessibility permissions.
  • Use peekaboo see --annotate to identify targets before clicking.

GitHub Repository

steipete/clawdis
Path: skills/peekaboo
relaywhatsapp

Related Skills

content-collections

Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill

creating-opencode-plugins

Meta

This skill provides the structure and API specifications for creating OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It offers implementation patterns for JavaScript/TypeScript modules that intercept and extend the AI assistant's lifecycle. Use it when you need to build event-driven plugins for monitoring, custom handling, or extending OpenCode's capabilities.

View skill

sglang

Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill

langchain

Meta

LangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.

View skill