Computer Use Automation

Category: Engineering Domain: AI Agents

Overview

The Computer Use Automation skill helps you design AI agents that operate a graphical interface the way a person does — take a screenshot, reason about what is on screen, then click, type, scroll, or navigate, and repeat. It covers the core perception→reason→action loop, the decision of when computer-use is the right tool versus a structured API/MCP tool (prefer a real API whenever one exists; reach for computer-use only for GUIs with no programmatic surface), reliability patterns (grounding every action in the current screenshot, verifying after each step, recovering from misclicks), safety guardrails (confirmation gates for destructive actions, sandboxing, avoiding blocking dialogs), and how to evaluate a computer-use agent. It is model-agnostic — the patterns apply to any computer-use-capable model and any GUI tool surface.

Clarify First

Before designing or auditing a computer-use agent, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Does a real API/MCP tool exist? — whether the target exposes an API, SDK, CLI, or MCP server, or is GUI-only (the single biggest factor; if a real API exists, prefer it and skip computer-use)
• Task & risk — what the agent must accomplish and whether any step is destructive or irreversible (delete, send, pay, submit), which sets the confirmation gates and sandboxing
• Which tool — advise on tool choice for a target, or lint a planned action sequence for safety (selects tool_choice_advisor.py vs action_safety_linter.py)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.