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 zavora-ai/computer-use-mcp --skill computer-use-formsgit clone --depth 1 https://github.com/zavora-ai/computer-use-mcpWrote 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/zavora-ai/computer-use-mcp/computer-use-forms)<a href="https://agentmods.dev/skills/zavora-ai/computer-use-mcp/computer-use-forms"><img src="https://agentmods.dev/badge/skills/zavora-ai/computer-use-mcp/computer-use-forms/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/zavora-ai/computer-use-mcp/computer-use-forms"><img src="https://agentmods.dev/badge/skills/zavora-ai/computer-use-mcp/computer-use-forms.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.00850 |
| Opus 5.5 | $0.00014 | $0.00340 |
| Sonnet 5.5 | $0.00007 | $0.00170 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
computer-use-forms 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Operating controls
Goal: put a value in the right field, and know that it landed.
Order of preference. Each step down is slower and less certain, so only take it when the one above cannot do the job:
- Accessibility —
fill_form,set_value,click_element. Native apps, and a browser's own chrome including its dialogs. - The page — a browser-automation server acting by selector, or
browser_findfor an element's exact screen coordinates. Anything inside a web page. - OCR (macOS) —
read_window_textwith aregion, thenclick_texton a label. Apps that draw their own UI have an empty accessibility tree; OCR needs no coordinates and works on a covered window.wait_for_textconfirms a value or a message appeared. - Pixels —
screenshot, thenclickandtype. A canvas, a custom-drawn control, an app that exposes nothing, text OCR cannot read.
Facts you cannot infer, each measured
A browser exposes its own controls, never its pages. Measured on Chrome showing a
web app: 37 accessible nodes, one text field — the address bar. A page input returns
[] rather than an error, so two empty searches means stop searching, not search
harder. Toolbar buttons and dialogs like "Save password?" are accessible.
A capture is smaller than the screen. 2560 wide arrives 1024 wide, so one image
pixel is 2.5 real ones, against a field about 35 pixels tall. Every screenshot reply
states its own mapping — read it rather than deriving one. On macOS 14+ a window
capture is the window alone, without its shadow, so the mapping is exact; on older
systems and other platforms a window capture can include a shadow and its scale is
approximate. A window that could not be captured silently becomes a screen capture, and
the reply says so. With a session target set, screenshot captures that window;
full_screen: true captures the screen.
zoom returns 1:1. Without a target it takes desktop coordinates, so raise the
window first or you will capture whatever else is at those coordinates. With
target_app or target_window_id (since 7.5) the region is in that window's points,
from its top-left.
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 Changed · +8 lines d96342381bac
- 1mo ago Changed · +44 lines · +8 tokens per session 4800e69c4c72
- 1mo ago First seen · 15 lines · 26 tokens per session scan A f72ecd171f79
computer-use-forms is a skill published in the GitHub repository zavora-ai/computer-use-mcp (86 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 850 once invoked, about $0.0001 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 2026-08-30.
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