OpenLoomi is an open-source desktop AI coworker that connects work tools, gathers context, and highlights decisions or actions needing attention. It is for people managing work across multiple apps, and its catalogue add-ons extend the resident desktop for agent frameworks such as Claude Code, Codex, OpenCode, Hermes, and OpenClaw.
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 melandlabs/openloomi --skill agent-browsergit clone --depth 1 https://github.com/melandlabs/openloomiWrote 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/melandlabs/openloomi/agent-browser)<a href="https://agentmods.dev/skills/melandlabs/openloomi/agent-browser"><img src="https://agentmods.dev/badge/skills/melandlabs/openloomi/agent-browser.svg" alt="Measured on agentmods" 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 | $0.00108 | $0.03853 |
| Opus 5 | $0.00054 | $0.01927 |
| Sonnet 5 | $0.00022 | $0.00771 |
| Haiku 4.5 | $0.00011 | $0.00385 |
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 7d 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.
This is a copy
72% identical to agent-browser — 155 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 467 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Browser Automation with agent-browser
Installation
Global Installation (recommended)
Installs the native Rust binary for maximum performance:
npm install -g agent-browser
agent-browser install # Download Chromium
This is the fastest option -- commands run through the native Rust CLI directly with sub-millisecond parsing overhead.
Quick Start (no install)
Run directly with npx if you want to try it without installing globally:
npx agent-browser install # Download Chromium (first time only)
npx agent-browser open example.com
Note:
npxroutes through Node.js before reaching the Rust CLI, so it is noticeably slower than a global install. For regular use, install globally.
Homebrew (macOS)
brew install agent-browser
agent-browser install # Download Chromium
Linux Dependencies
On Linux, install system dependencies:
agent-browser install --with-deps
# or manually: npx playwright install-deps chromium
Core Workflow
Every browser automation follows this pattern:
- 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
# Output: @e1 [input type="email"], @e2 [input type="password"], @e3 [button] "Submit"
agent-browser fill @e1 "[email protected]"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait --load networkidle
agent-browser snapshot -i # Check result
Command Chaining
Commands can be chained with && in a single shell invocation. The browser persists between commands via a background daemon, so chaining is safe and more efficient than separate calls.
# Chain open + wait + snapshot in one call
agent-browser open https://example.com && agent-browser wait --load networkidle && agent-browser snapshot -i
# Chain multiple interactions
agent-browser fill @e1 "[email protected]" && agent-browser fill @e2 "password123" && agent-browser click @e3
# Navigate and capture
agent-browser open https://example.com && agent-browser wait --load networkidle && agent-browser screenshot page.png
What ships with it
8 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.
- references/authentication.md 4.3 KB
- references/proxy-support.md 4.2 KB
- references/session-management.md 3.8 KB
- references/snapshot-refs.md 4.0 KB
- references/video-recording.md 3.2 KB
- templates/authenticated-session.sh 4.1 KB runs code
- templates/capture-workflow.sh 1.9 KB runs code
- templates/form-automation.sh 1.6 KB runs code
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.
- 7d ago First seen · 467 lines · 108 tokens per session scan A 6fa76ed124c9
agent-browser is a skill published in the GitHub repository melandlabs/openloomi (1,021 stars, last pushed 6d ago), licensed Apache-2.0. It adds 108 tokens to every session and 3,853 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 72% identical to agent-browser, differing in 155 lines, and is treated as a copy.
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