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 jnPiyush/AgentX --skill computer-use-and-browser-agentsgit clone --depth 1 https://github.com/jnPiyush/AgentXWrote 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/jnpiyush/agentx/computer-use-and-browser-agents)<a href="https://agentmods.dev/skills/jnpiyush/agentx/computer-use-and-browser-agents"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/computer-use-and-browser-agents/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/jnpiyush/agentx/computer-use-and-browser-agents"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/computer-use-and-browser-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 96 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00068 | $0.01166 |
| Opus 5.5 | $0.00027 | $0.00466 |
| Sonnet 5.5 | $0.00014 | $0.00233 |
| Haiku 4.5 | $0.00007 | $0.00117 |
Grade A, and why
computer-use-and-browser-agents 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 1mo 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Computer Use and Browser Agents
Purpose: Drive a browser or desktop reliably from an LLM, without leaking credentials, taking unsafe actions, or stalling on unfamiliar UI.
When to Use This Skill
- Automating workflows in apps that have no API
- Web scraping behind login, multi-step forms, captchas (where allowed)
- QA / test automation by LLM
- Internal RPA replacements
- Research agents that browse the open web
When NOT to Use
- A stable API exists -> use it; computer-use is slow, costly, brittle
- High-frequency / sub-second tasks -> too slow
- Strict legal / ToS constraints on automation
Approach Spectrum
[Screenshot + LLM] <----- visual grounding -----> [DOM + LLM]
Anthropic Computer Use browser-use
OpenAI CUA / Operator Playwright + LLM
Most desktop agents Most web-only agents
Visual approach: works on any UI but expensive (vision tokens, latency). DOM approach: cheaper and more reliable on web; fails on canvas/PDF/video.
Hybrid is common: DOM where possible, screenshot fallback for non-DOM regions.
Tool Surface
Typical action set:
| Action | Args |
|---|---|
screenshot |
(returns image) |
click |
x, y or selector |
type |
text |
key |
key combo (Ctrl+L, Tab, Enter) |
scroll |
direction, amount |
navigate |
url |
wait |
ms or until-condition |
read_page |
(returns DOM-text or accessibility tree) |
Anthropic Computer Use exposes computer, text_editor, bash. OpenAI CUA exposes computer. browser-use exposes a richer DOM-aware set.
Sandboxing (Required)
Never run computer-use against your own session, machine, or production browser profile.
| Sandbox | Use |
|---|---|
| E2B, Browserbase, Scrapybara, Hyperbrowser | Managed sandboxed browsers/desktops |
| Docker container with Chrome + Xvfb | Self-hosted, ephemeral |
| Dedicated VM | Strongest isolation |
| Ephemeral browser profile | Per-task, deleted after |
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.
- 1mo ago Changed 7ebf0322ba89
- 1mo ago First seen · 147 lines · 68 tokens per session scan A 4fabb6d6eb77
computer-use-and-browser-agents is a skill published in the GitHub repository jnPiyush/AgentX (17 stars, last pushed 2d ago), licensed Apache-2.0. It adds 68 tokens to every session and 1,166 once invoked, about $0.0003 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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