Openclaw Web Browser

웹사이트 브라우징, 정보 수집, 데이터 추출, 모니터링을 위한 종합 브라우징 스킬. 정적/동적 웹페이지에서 데이터를 수집하고 JSON으로 구조화하며, 변경사항 모니터링과 정기 수집을 지원한다. 항공(ICAO, FAA 등) 기관 수집에 특화된 프리셋도 포함.

This package is internally consistent with a web-scraping and monitoring toolkit, but review these points before installing or running: 1) Dependencies: ensure you run in a controlled Python environment (virtualenv) and install requests and beautifulsoup4 as the code expects. 2) robots.txt & site policy: fetcher.py checks robots.txt, but monitor.py does not; SKILL.md encourages using a browser session when bot-detection or robots.txt blocks exist — that behavior could be interpreted as attempting to bypass site rules. Decide whether you want monitoring to respect robots.txt and adjust the code. 3) Data handling: the monitor stores snapshots and diffs locally (monitor-data/) and the doc-recommender supports uploading/reading collection JSONs — sanitize any sensitive content before sharing with other services or models. 4) Rate and legality: the tool can be run on schedules (cron examples are included); tune rate limits and check target sites' terms-of-service and legal restrictions (esp. automated scraping of search engines). 5) Run first in a sandbox: because the package executes network requests and writes files, run it in a sandbox/container or VM until you’ve inspected/modified behavior you don’t want (robots handling, cron entries, where data is stored). If you want, I can: (a) point out exact lines in monitor.py to add robots.txt checks; (b) produce a minimal requirements.txt and a safe-run checklist; or (c) scan the remaining truncated code for other issues if you provide it.

Type: OpenClaw Skill Name: web-browser-toolkit Version: 1.0.0 The 'web-browser-toolkit' is a legitimate and well-documented utility for web scraping, monitoring, and regulatory document recommendation, specifically tailored for the aviation industry (ICAO, FAA, EASA). The bundle includes functional Python scripts such as fetcher.py for structured data extraction, monitor.py for tracking website changes, and doc_recommender.py for matching content against a regulatory knowledge base. The code follows responsible scraping practices, including robots.txt verification and rate limiting, and lacks any indicators of malicious intent, data exfiltration, or harmful prompt injection.