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 agentmods add skills/metahub-tech/agent-fleet/using-human-browsernpx skills add metahub-tech/agent-fleet --skill using-human-browsergit clone --depth 1 https://github.com/metahub-tech/agent-fleetWrote 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/metahub-tech/agent-fleet/using-human-browser)<a href="https://agentmods.dev/skills/metahub-tech/agent-fleet/using-human-browser"><img src="https://agentmods.dev/badge/skills/metahub-tech/agent-fleet/using-human-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 | $0.00090 | $0.01681 |
| Opus 5 | $0.00045 | $0.00840 |
| Sonnet 5 | $0.00018 | $0.00336 |
| Haiku 4.5 | $0.00009 | $0.00168 |
Grade A, and why
using-human-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 4d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using human_browser
human_browser is a self-built capability: it launches the host's real daily Google Chrome with no debug port and no automation flags, so there are zero automation traces — navigator.webdriver stays false, there is no CDP interface to probe, and input is genuine OS-level input. You then operate the page the way a person does: look at a screenshot, click coordinates, type.
This is the moat: it reuses the device's OS-level control (core tools), not a browser-automation framework.
human_browser vs agent_browser (routing)
- human_browser (this skill): real Chrome, real logged-in identity, zero automation traces. Page localization:
human_dom(read-only DOM locator companion — exact coordinates, see using-human-dom) or screenshot+coordinates. Use when acting as the human on real accounts / identity. - agent_browser: Playwright-driven, DOM snapshot+ref, fast — but has automation traces and uses an isolated profile (NOT the human's identity, NOT the user's login). Use for testing / scraping / browsing-to-learn on throwaway isolated profiles.
★ Rule for real accounts (read this — it's the #1 footgun): a real account / identity → human_browser + human_dom, from the FIRST navigation (including the login scan) through every op. NEVER touch agent_browser for that account — not even to "just browse and check" first. Why: agent_browser logs into its isolated profile (~/.fleet/agent-browser-profile), invisible to human_browser; if you scan/login there, your later human_browser runs see a logged-OUT browser → you re-login forever (this was a real bug: a publisher re-scanned every hour for 12h). human_dom now gives human_browser DOM-level precision, so there is no reason to use agent_browser on a real account.
登录态跨 run 持久 + resume（recurring operator 必读）
A recurring operator (an agent driving a real account every run / cron tick) must reuse ONE login across runs — the user scans once, not every run:
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.
- 4d ago First seen · 47 lines · 90 tokens per session scan A c05593159d82
using-human-browser is a skill published in the GitHub repository metahub-tech/agent-fleet (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,681 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
bootstrap-repo-analysis
First-time analysis of a repository with no prior reviewer outcomes. Crawl historical merged-PR review feedback with the gh CLI (plus any preloaded samples), extract the team's review norms, and synthesize the initial per-repo review-style prompt. Use this for a cold-start repo; use continual-learning instead once the…
browserwing-executor
Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.
dev-browser
Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website"…
browse
Use the browse CLI for Browserbase browser automation, Browserbase cloud APIs, Browserbase Functions, templates, web fetch/search, diagnostics, and Browse.sh skill discovery/installation. Use when the user asks to navigate pages, inspect browser state, run local or remote browser sessions, manage Browserbase…
browserwing-admin
Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.
agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a…