This skill provides workflows and tools to collect, filter, and summarize the latest developments in the AI industry across major platforms.
Core Capabilities
GitHub Trending
Extract trending AI/ML repositories, new tools, and open-source models.
X (Twitter) Updates
Gather updates from key AI researchers, organizations, and trending AI hashtags.
News Aggregation
Summarize top AI headlines from tech news sources.
Digest Generation
Compile the collected information into a structured, easy-to-read markdown digest.
Workflows
1. Generating a Daily AI Digest
When a user requests a daily AI news summary, follow this process:
Information Gathering
:
MUST RESTRICT SEARCH TO THE LAST 7 DAYS. Use explicit date filters (e.g., in
curl
or
web_search
) to ensure no news or repositories older than one week are included.
Use the web search tool to find the current GitHub trending repositories (filter by spoken language or programming language like Python/Jupyter Notebook).
Search for recent AI news using queries like "AI news today", "latest artificial intelligence developments", or specific topics (e.g., "OpenAI news", "new LLM releases").
If applicable and accessible, search for trending AI discussions on X (Twitter).
Filtering & Curation
:
Filter out noise and generic news.
Focus on: New model releases, significant open-source projects, major industry announcements, breakthrough research, and trending developer tools.
STRICTLY exclude any items older than 7 days.
Formatting the Digest
:
Use the template provided in
references/digest-template.md
to structure the output.
Group items logically (e.g., Open Source & GitHub, Industry News, Research & Papers).
Provide brief, 1-2 sentence summaries for each item.
MANDATORY
Every single news item, repository, paper, or tweet MUST include its original source URL as a markdown link