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 Kevin-Liu-01/Agent-Machines --skill agent-browsergit clone --depth 1 https://github.com/Kevin-Liu-01/Agent-MachinesWrote 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/kevin-liu-01/agent-machines/agent-browser)<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/agent-browser"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/agent-browser/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/kevin-liu-01/agent-machines/agent-browser"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/agent-browser.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 | $0.00080 | $0.01046 |
| Opus 5.5 | $0.00032 | $0.00418 |
| Sonnet 5.5 | $0.00016 | $0.00209 |
| Haiku 4.5 | $0.00008 | $0.00105 |
Grade A, and why
agent-browser 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Browser Automation with agent-browser
CLI browser automation via Chrome/Chromium CDP. Install: npm i -g agent-browser. Run agent-browser install to download Chrome.
Core Workflow
- Navigate:
agent-browser open <url> - Snapshot:
agent-browser snapshot -i(get element refs like@e1,@e2) - Interact: Use refs to click, fill, select
- Re-snapshot: After navigation or DOM changes, get fresh refs
agent-browser open https://example.com/form
agent-browser snapshot -i
agent-browser fill @e1 "[email protected]"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait 2000
agent-browser snapshot -i
Batch Execution
ALWAYS use batch for 2+ sequential commands:
agent-browser batch "open https://example.com" "snapshot -i"
agent-browser batch "click @e1" "wait 1000" "screenshot"
agent-browser batch "open https://example.com" "snapshot -i" "screenshot"
Only run a single command when you need to read output before deciding the next step.
Essential Commands
# Navigation
agent-browser open <url>
agent-browser close
agent-browser close --all
# Snapshot (get interactive element refs)
agent-browser snapshot -i
agent-browser snapshot -i --urls # Include href URLs for links
agent-browser snapshot -s "#selector" # Scope to CSS selector
# Interaction (use @refs from snapshot)
agent-browser click @e1
agent-browser fill @e2 "text"
agent-browser select @e1 "option"
agent-browser press Enter
agent-browser scroll down 500
# Get information
agent-browser get text @e1
agent-browser get url
agent-browser get title
# Wait
agent-browser wait @e1 # Wait for element
agent-browser wait 2000 # Wait milliseconds
agent-browser wait --text "Welcome" # Wait for text
agent-browser wait --url "**/page" # Wait for URL pattern
# Capture
agent-browser screenshot
agent-browser screenshot --full # Full page
agent-browser screenshot --annotate # With numbered element labels
agent-browser pdf output.pdf
# Diff (verify changes)
agent-browser diff snapshot # Compare current vs last snapshot
agent-browser diff screenshot --baseline before.png
# Tab management
agent-browser tab list
agent-browser tab new https://example.com
agent-browser tab 2
agent-browser tab close
# Sessions
agent-browser --session site1 open https://site-a.com
agent-browser session list
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 First seen · 149 lines · 80 tokens per session scan A 5ac3974a079e
agent-browser is a skill published in the GitHub repository Kevin-Liu-01/Agent-Machines (30 stars, last pushed 3d ago), licensed MIT. It adds 80 tokens to every session and 1,046 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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