ai-research-scraper_skill

Overview

This skill scrapes recent AI research and product-development news from reputable AI sites and returns concise summaries with source links. It limits output size and token usage so results are quick to read and easy to scan. The tool supports configurable site lists, periodic updates, and simple caching to reduce redundant requests.

How this skill works

The scraper fetches articles from a curated list of AI-focused sources, extracts key product-development details, and generates short summaries while preserving original links. It enforces maximum token limits, adds retries and extended timeouts for reliability, and uses a one-hour cache to avoid duplicate retrievals. The scraper can be run on-demand or scheduled for regular updates and accepts options for time range, topic focus, and summary length.

When to use it

• Quickly catch up on the latest AI product announcements across major outlets.
• Track developments for a specific AI product or company over recent days or weeks.
• Get compact research summaries for inclusion in newsletters or briefings.
• Run automated daily or weekly pulls to feed downstream monitoring tools.
• Reduce noisy full-article reads when you only need product-focused highlights.

Best practices

• Maintain and curate the websites.txt list to include only stable, high-signal sources.
• Set conservative max-token limits to keep summaries scannable and consistent.
• Use the --days option to restrict results to a meaningful recent window.
• Enable the one-hour cache for scheduled runs to avoid redundant scraping.
• Add or swap sources gradually and verify parsing rules for new site structures.

Example use cases

• Daily digest: schedule the scraper to collect and summarize product news for a morning briefing.
• Product research: pull recent announcements and feature changes for a competitor analysis.
• Newsletter sourcing: collect concise research highlights and link back to original posts.
• Engineering sync: feed short summaries into a team channel to signal relevant AI product updates.
• Archival backup: periodically archive summaries and original URLs as a lightweight snapshot of AI news.