Fetch AtCoder problem statements and editorials into Markdown.
npx skills add https://github.com/paruma/atcoder_rust --skill atcoder-fetcher
Please help me install this Agent Skill. Skill: atcoder-fetcher Source: https://github.com/paruma/atcoder_rust/tree/main/.gemini/skills/atcoder-fetcher Command: npx skills add https://github.com/paruma/atcoder_rust --skill atcoder-fetcher
This skill fetches and formats AtCoder problem statements and editorials from URLs into clean Markdown for easy reading, sharing, or integration into notes.
Run the AtCoder Fetcher to convert a problem page or editorial page to Markdown.
High-intent search queries and answers about installing and using this skill.
To convert AtCoder problem statements to Markdown, provide a direct task URL to the fetcher script. It parses the HTML using BeautifulSoup4 and outputs clean, readable Markdown ready for your study notes.
Yes, you can fetch AtCoder editorials by passing an editorial URL to the fetch script. It extracts the content and formats it into consistent Markdown for local reading and integration into documents.
The AtCoder fetcher requires Python 3.11+ and depends on the BeautifulSoup4 and requests libraries. You must also ensure environment variables like UV_CACHE_DIR and PATH are configured before running the scripts.
The best way to scrape AtCoder content is using a dedicated fetcher script leveraging requests and BeautifulSoup4 to parse HTML. It handles URL construction and outputs formatted Markdown directly for your templates.
Yes, the fetcher supports problem-name based URL construction to retrieve AtCoder problem statements. This allows you to generate the correct task URL and fetch formatted Markdown without needing the exact link beforehand.
Using requests and BeautifulSoup4 for AtCoder web scraping limits you to static HTML parsing, meaning dynamically loaded content will not be captured. It outputs consistent Markdown but cannot execute JavaScript-rendered page elements.
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