Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add X-School-Academy/skill-pilot --skill use-computergit clone --depth 1 https://github.com/X-School-Academy/skill-pilotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/x-school-academy/skill-pilot/use-computer)<a href="https://agentmods.dev/skills/x-school-academy/skill-pilot/use-computer"><img src="https://agentmods.dev/badge/skills/x-school-academy/skill-pilot/use-computer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/x-school-academy/skill-pilot/use-computer"><img src="https://agentmods.dev/badge/skills/x-school-academy/skill-pilot/use-computer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.00705 |
| Opus 5.5 | $0.00016 | $0.00282 |
| Sonnet 5.5 | $0.00008 | $0.00141 |
| Haiku 4.5 | $0.00004 | $0.00071 |
Grade A, and why
use-computer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 16d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use Computer
This skill enables an agent to interact with the computer's graphical user interface (GUI). It can retrieve screen information, take screenshots of specific regions, and perform mouse and keyboard actions.
When to Use This Skill
- User needs to interact with GUI applications programmatically
- User asks to automate mouse and keyboard actions
- User wants to take screenshots of specific screen regions
- User needs to test UI flows or perform visual verification
- User requires automated interaction with desktop applications
Your Roles in This Skill
- QA Engineer: Use computer control to perform automated UI testing and verification. Take screenshots to capture UI states and verify visual elements. Execute test scripts that require GUI interaction. Verify application behavior through visual feedback.
- DevOps Engineer: Execute Python scripts for computer control operations. Manage system permissions for screen recording and accessibility. Configure screen coordinates and interaction parameters. Troubleshoot PyAutoGUI fail-safe and permission issues.
Role Communication
As an expert in your assigned roles, you must announce your actions before performing them using the following format:
As a {Role} [and {Role}, ...], I will {action description}
This communication pattern ensures transparency and allows for human-in-the-loop oversight at key decision points.
Instructions
All interactions are performed via the core/bin/use-computer CLI from the project root:
core/bin/use-computer --json_str '<JSON_COMMAND>'
The script returns a JSON response wrapped in <output></output> tags.
1. Get Screen Information
Use this to understand the monitor setup and primary screen resolution.
Command:
{"action": "screen_info"}
2. Take a Screenshot
For screenshot payloads, return fields, scaling, pointer markers, and coordinate correction, refer to references/screenshot.md.
3. Find Coordinates for Actions (Required)
Before any mouse_move or click, use agent skill find-ui-element to locate the target UI element and derive coordinates.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 16d ago First seen · 72 lines · 39 tokens per session scan A 08e3ce77ed7e
use-computer is a skill published in the GitHub repository X-School-Academy/skill-pilot (20 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 705 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
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