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 bestagentkits/agency-skills --skill browser-automationgit clone --depth 1 https://github.com/bestagentkits/agency-skillsWrote 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/bestagentkits/agency-skills/browser-automation)<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/browser-automation"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/browser-automation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/browser-automation"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/browser-automation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00046 | $0.03025 |
| Opus 5 | $0.00023 | $0.01512 |
| Sonnet 5 | $0.00009 | $0.00605 |
| Haiku 4.5 | $0.00005 | $0.00302 |
Grade A, and why
browser-automation 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 11d 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Browser Automation - POWERFUL
Overview
The Browser Automation skill provides comprehensive tools and knowledge for building production-grade web automation workflows using Playwright. This skill covers data extraction, form filling, screenshot capture, session management, and anti-detection patterns for reliable browser automation at scale.
When to use this skill:
- Scraping structured data from websites (tables, listings, search results)
- Automating multi-step browser workflows (login, fill forms, download files)
- Capturing screenshots or PDFs of web pages
- Extracting data from SPAs and JavaScript-heavy sites
- Building repeatable browser-based data pipelines
When NOT to use this skill:
- Writing browser tests or E2E test suites — use playwright-pro instead
- Testing API endpoints — use api-test-suite-builder instead
- Load testing or performance benchmarking — use performance-profiler instead
Why Playwright over Selenium or Puppeteer:
- Auto-wait built in — no explicit
sleep()orwaitForElement()needed for most actions - Multi-browser from one API — Chromium, Firefox, WebKit with zero config changes
- Network interception — block ads, mock responses, capture API calls natively
- Browser contexts — isolated sessions without spinning up new browser instances
- Codegen —
playwright codegenrecords your actions and generates scripts - Async-first — Python async/await for high-throughput scraping
Core Competencies
1. Web Scraping Patterns
Selector priority (most to least reliable):
data-testid,data-id, or custom data attributes — stable across redesigns#idselectors — unique but may change between deploys- Semantic selectors:
article,nav,main,section— resilient to CSS changes - Class-based:
.product-card,.price— brittle if classes are generated (e.g., CSS modules) - Positional:
nth-child(),nth-of-type()— last resort, breaks on layout changes
Use XPath only when CSS cannot express the relationship (e.g., ancestor traversal, text-based selection).
What ships with it
7 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.
- agents/openai.yaml 213 B
- references/anti_detection_patterns.md 14 KB
- references/data_extraction_recipes.md 19 KB
- references/playwright_browser_api.md 13 KB
- scripts/anti_detection_checker.py 22 KB runs code
- scripts/form_automation_builder.py 9.9 KB runs code
- scripts/scraping_toolkit.py 7.6 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.
- 11d ago First seen · 267 lines · 46 tokens per session scan A 7d6daa1f3f88
browser-automation is a skill published in the GitHub repository bestagentkits/agency-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 3,025 once invoked, about $0.0002 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.
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