# Benchmark browser agents on a fixed stealth and task suite with browser-use benchmark > Compare browser-agent reliability on a repeatable task and anti-bot suite before choosing a stack or claiming progress. - Skill: `agentskillexchange/benchmark-browser-agents-on-a-fixed-stealth-and-task-suite-w` (Agent Skill) - Install (CLI): `npx skillmds@latest add agentskillexchange/benchmark-browser-agents-on-a-fixed-stealth-and-task-suite-w` - Raw SKILL.md: https://api.skillmd.com/api/skills/agentskillexchange/benchmark-browser-agents-on-a-fixed-stealth-and-task-suite-w/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: agentskillexchange (https://skillmd.com/u/agentskillexchange) - Updated: 2026-09-08 - Page: https://skillmd.com/skills/agentskillexchange/benchmark-browser-agents-on-a-fixed-stealth-and-task-suite-w --- # Benchmark browser agents on a fixed stealth and task suite with browser-use benchmark Compare browser-agent reliability on a repeatable task and anti-bot suite before choosing a stack or claiming progress. ## Prerequisites Python, uv, benchmark repository dependencies, required API keys for the judge model and selected browser provider, target browser agent configuration ## Installation Use the upstream install or setup path that matches your environment: - pip install uv - uv sync - uv run python run_eval.py --browser Requirements and caveats from upstream: - python -c " Basic usage or getting-started notes: - **2. Set up your .env** (see [.env.example](.env.example)) - cp .env.example .env - **4. Run the evaluation** - Source: https://github.com/browser-use/benchmark - Extracted from upstream docs: https://raw.githubusercontent.com/browser-use/benchmark/HEAD/README.md ## Documentation - https://github.com/browser-use/benchmark#readme ## Source - [Agent Skill Exchange](https://agentskillexchange.com/skills/benchmark-browser-agents-on-a-fixed-stealth-and-task-suite-with-browser-use-benchmark/)