Browser4 is an AI-native browser engine that lets autonomous agents and people control real browsers, extract information from web pages, and automate tasks at scale. It combines browser interaction through a Rust CLI and MCP with deterministic selectors, machine-learning clustering, and language-model extraction. The catalogue entries provide skills and instructions for using Browser4.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/platonai/Browser4npx agentmods add skills/platonai/browser4/coworkerWrote 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/platonai/browser4/coworker)<a href="https://agentmods.dev/skills/platonai/browser4/coworker"><img src="https://agentmods.dev/badge/skills/platonai/browser4/coworker.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 | $0.00050 | $0.04343 |
| Opus 5 | $0.00025 | $0.02171 |
| Sonnet 5 | $0.00010 | $0.00869 |
| Haiku 4.5 | $0.00005 | $0.00434 |
Grade A, and why
coworker 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.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coworker
This repository contains a file-queue automation system called Coworker. The active implementation is the PowerShell worker in coworker/scripts/engineer.ps1: it watches task files, renames them, runs GitHub Copilot against the repository, logs the run, and routes the task through review/approval/push folders. (coworker/README.md:1-40, coworker/scripts/engineer.ps1:50-80, coworker/scripts/engineer.ps1:413-717)
What Coworker is for
- Use Coworker when you want an agentic workflow driven by task files in the repo, not by chat alone.
- A task can be a plain Markdown file or a structured file with
Title:,Description:, andPrompt:. If the structured header is missing, the full file becomes the prompt. (coworker/scripts/engineer.ps1:11-20,coworker/scripts/engineer.ps1:536-541) - The worker runs GitHub Copilot CLI with broad repo access to execute the task against the current repository. The helper command is configurable in
coworker/scripts/config.psd1. (coworker/scripts/workers/gh-copilot.ps1:37-65,coworker/scripts/config.psd1:1-12) - Important: the current/live workflow is file-based. The folder-based “story.md / analysis / plan / design / impl.patch / e2e” pipeline described in
coworker/docs/architect/orchestrator.mdandcoworker/scripts/architect/orchestrator.ps1exists as design/legacy material, but it is not the main coworker entrypoint used bycoworker.ps1. (coworker/docs/architect/orchestrator.md:1-38,coworker/scripts/architect/orchestrator.ps1:17-29,coworker/scripts/engineer.ps1:57-68)
Main workflows and scripts
1. Main task execution
- Primary entrypoint:
./coworker/scripts/engineer.ps1 - It ensures the task directories exist, optionally accepts a task file path, moves that file into
coworker/tasks/main/1ready, generates a descriptive kebab-case filename, moves it to2working, runs Copilot, writes logs, then moves the task tomain/3completeor5approved. (coworker/scripts/engineer.ps1:22-35,coworker/scripts/engineer.ps1:82-95,coworker/scripts/engineer.ps1:417-500,coworker/scripts/engineer.ps1:551-713) - The prompt given to Copilot explicitly says: finish the task described in the file, but do not move that task file yourself. The script handles routing after execution. (
coworker/scripts/engineer.ps1:531-545)
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 · 186 lines · 50 tokens per session scan A 066c4e835e42
coworker is a skill published in the GitHub repository platonai/Browser4 (1,122 stars, last pushed today), licensed Apache-2.0. It adds 50 tokens to every session and 4,343 once invoked, about $0.0003 per session on Opus 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.
Other skills, from other repositories
eric-task-master
Run durable local Chrome automation with the installed Task Master CLI. Use when an Agent needs to create and execute a one-off browser task, follow its progress, or manage its Chrome Profile.
worker-integration
Worker-Agent integration for intelligent task dispatch and performance tracking.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
jetson-diagnostic
Read-only Jetson health snapshot for identity, memory, GPU, thermal, power, storage, services, and top processes.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.