github-trending

To find today's trending AI and LLM projects on GitHub, this Skill fetches the GitHub trending page and filters repositories by AI, LLM, agent, and ML topics. It returns a structured JSON array containing the project name, URL, stars, topics, and description for quick research and monitoring.

Yes, you can get a structured JSON list of GitHub trending repositories filtered by machine learning topics. The Skill parses the GitHub trending page, extracts repository metadata like names and stars, applies an AI/ML topic filter, and emits the formatted JSON array directly to stdout.

The best way to automate daily discovery of trending AI agent repositories for a tech radar is to use this Skill. It automatically fetches the daily GitHub trending list, extracts repository details, filters for AI agent topics, and outputs a structured JSON array suitable for building a tech radar.

Yes, this GitHub trending Skill extracts repository stars and descriptions for open-source scouting. It parses the trending page to capture the repository name, URL, star count, topics, and description, providing a structured JSON output ideal for side-project scouting and competitive awareness.

When parsing GitHub trending data for LLM and ML projects, the included data fields are the repository name, URL, total stars, associated topics, and the project description. These fields are structured into a JSON array emitted to stdout for immediate integration into your data pipeline.

A limitation when fetching GitHub trending projects filtered by specific AI topics is that the Skill relies entirely on parsing the public GitHub trending page. It filters based on the topics present on that page, meaning it only captures daily trends and does not query custom historical date ranges or private repositories.