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 billy-enrizky/openbrowser-ai --skill page-analysisgit clone --depth 1 https://github.com/billy-enrizky/openbrowser-aiWrote 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/billy-enrizky/openbrowser-ai/page-analysis)<a href="https://agentmods.dev/skills/billy-enrizky/openbrowser-ai/page-analysis"><img src="https://agentmods.dev/badge/skills/billy-enrizky/openbrowser-ai/page-analysis.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 | $0.00066 | $0.02053 |
| Opus 5 | $0.00033 | $0.01026 |
| Sonnet 5 | $0.00013 | $0.00411 |
| Haiku 4.5 | $0.00007 | $0.00205 |
Grade C, and why
page-analysis scanned grade C with 2 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 8d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://raw.githubusercontent.com/billy-enrizky/openbrowser-ai/main/install.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(openbrowser-ai:*) Bash(curl:*) Bash(uv:*) Bash(irm:*) Read Write How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Page Analysis
Analyze and understand web page content, structure, and interactive elements using Python code execution. Produces a comprehensive breakdown of what is on the page and how it is organized.
All code runs via openbrowser-ai -c. The daemon starts automatically and persists variables across calls. All browser functions are async -- use await.
The CLI daemon also persists cookies and login state in ~/.config/openbrowser/profiles/daemon/storage_state.json, so authenticated sessions can be reused across later runs.
Setup
Before running, verify openbrowser-ai is installed:
openbrowser-ai --help
If not found, install:
# macOS/Linux
curl -fsSL https://raw.githubusercontent.com/billy-enrizky/openbrowser-ai/main/install.sh | sh
# Windows (PowerShell)
irm https://raw.githubusercontent.com/billy-enrizky/openbrowser-ai/main/install.ps1 | iex
Workflow
Step 1 -- Navigate and get overview
openbrowser-ai -c - <<'EOF'
await navigate("https://example.com")
state = await browser.get_browser_state_summary()
print(f"Title: {state.title}")
print(f"URL: {state.url}")
print(f"Interactive elements: {len(state.dom_state.selector_map)}")
print(f"Tabs: {len(state.tabs)}")
EOF
Step 2 -- Extract page metadata
openbrowser-ai -c - <<'EOF'
meta = await evaluate("""
(function(){
return {
title: document.title,
description: document.querySelector("meta[name='description']")?.content,
canonical: document.querySelector("link[rel='canonical']")?.href,
ogTitle: document.querySelector("meta[property='og:title']")?.content,
ogImage: document.querySelector("meta[property='og:image']")?.content,
lang: document.documentElement.lang,
charset: document.characterSet
};
})()
""")
import json
print(json.dumps(meta, indent=2))
EOF
Step 3 -- Detect frameworks and technologies
openbrowser-ai -c - <<'EOF'
tech = await evaluate("""
(function(){
const t = [];
if (window.__NEXT_DATA__) t.push("Next.js");
if (window.__NUXT__) t.push("Nuxt.js");
if (document.querySelector("[data-reactroot]") || document.querySelector("#__next")) t.push("React");
if (document.querySelector("[ng-version]")) t.push("Angular");
if (window.jQuery) t.push("jQuery");
if (window.Vue) t.push("Vue.js");
if (document.querySelector("[data-svelte]")) t.push("Svelte");
return t;
})()
""")
print(f"Technologies detected: {tech}")
EOF
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.
- 8d ago First seen · 254 lines · 66 tokens per session scan C 57389da42326
page-analysis is a skill published in the GitHub repository billy-enrizky/openbrowser-ai (241 stars, last pushed 2mo ago), licensed MIT. It adds 66 tokens to every session and 2,053 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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