article-analysis

The article-analysis skill serves as an automated content consumption assistant, specifically designed to help users process and retain information from the web. By leveraging URL-based ingestion, the tool fetches content from sources such as Substack, Medium, personal blogs, and news sites, transforming raw web text into clean, structured knowledge. This skill is ideal for researchers, lifelong learners, and professionals who frequently curate online content but struggle with information overload or maintaining a consistent record of what they read.

• Automatically fetches webpage content using the integrated WebFetch utility.

• Generates standardized analysis reports in markdown, including article titles, source URLs, summary sections, key takeaways, and insights.

• Organizes reports into a dedicated library directory (reports/articles/) with timestamped, sanitized filenames.

• Maintains an automated activity log (logs/YYYY-MM-DD.md) to track reading history and facilitate daily reviews.

• Provides a consistent template for 'My Notes' to support active reading and personal annotations.

• Integrates seamlessly with slash commands like /read <url> for rapid activation within the Personal OS environment.

• Best used when dealing with long-form web content, newsletters, or technical blog posts where manual summarization is time-consuming.

• If automated fetching fails, the system provides clear fallback instructions to copy content manually into an inbox directory for local analysis.

• Ensure the input is a valid web URL or text file content; the tool handles cleanup and title extraction based on the provided prompt configuration (prompts/article.md).

• The skill acts as a bridge between transient web reading and permanent knowledge storage, making it a critical component of a digital personal knowledge base.