Content Cleaner Skill
This skill transforms noisy web content (like raw HTML dumps, messy copy-pastes with JSON/navigation, or URLs) into clean, readable Markdown articles.
Input Handling
- If the user provides a URL: Use the
read_url_contenttool or theagent-browserskill to fetch the raw page content. - If the user provides raw text or a file: Read the content directly.
Cleaning Guidelines
When processing the content, ALWAYS apply the following rules:
- Remove Noise: Strip out all website navigation menus, header/footer links, sidebar content, search bars, and "Log In / Subscribe" prompts.
- Remove Ads & Promos: Exclude all advertisement placeholders (e.g., "廣告-請繼續往下閱讀"), sponsored content blocks, related article links (e.g., "延伸閱讀", "相關文章"), and social media sharing buttons.
- Remove Metadata Bloat: Strip out raw JSON-LD (Schema.org) blocks, raw HTML tags, and unnecessary script code.
- Retain Core Information: Keep the main article title, author name, publication date (if available), and the complete article body. Keep all heading structures within the article body intact.
Output Format
ALWAYS format the final output as a clean Markdown file. Use this exact template:
# [Article Title]
**Author**: [Author Name or 'Unknown']
**Date**: [Publication Date or 'Unknown']
---
[Cleaned Article Body]
Saving the Output
Unless the user specifies otherwise, save the output to a clearly named Markdown file in a dated directory, for example: ./reports/Articles_YYYY_MM_DD/[source_name_snake_case].md. Do not summarize the entire article in the chat window; just provide the path to the saved file and a 1-sentence confirmation.