github-ai-trendsGenerate GitHub AI trending project reports as formatted text leaderboards. Fetches top-starred AI/ML/LLM repos by daily, weekly, or monthly period and renders a styled leaderboard. Use when the user asks for AI project trends, GitHub trending, AI leaderboard, or wants to see popular AI repos.
Install via ClawdBot CLI:
clawdbot install toller892/github-ai-trendsGenerate formatted leaderboard of trending AI projects on GitHub, output directly to chat.
Run the script and paste its stdout as the reply:
python3 scripts/fetch_trends.py --period weekly --limit 20--period: daily | weekly | monthly (default: weekly)--limit: Number of repos (default: 20)--token: GitHub token for higher rate limits (or set GITHUB_TOKEN env)--json: Output raw JSON instead of formatted textGenerated Mar 1, 2026
Researchers and data scientists use this skill to monitor emerging AI projects on GitHub, identifying cutting-edge tools and libraries for their work. It helps them stay updated on trends like new machine learning frameworks or LLM implementations, enabling faster adoption of innovative technologies in academic or industrial research.
Recruiters and HR professionals leverage this skill to discover popular AI projects and identify active developers contributing to trending repositories. This aids in sourcing top talent by analyzing project engagement and star counts, streamlining the hiring process for AI and software engineering roles.
Investors and analysts use this skill to track AI project trends on GitHub, assessing the popularity and growth of open-source initiatives for potential funding opportunities. It provides insights into community adoption and developer interest, supporting data-driven decisions in tech investments and startup evaluations.
Bloggers, journalists, and content creators utilize this skill to generate up-to-date reports on trending AI projects for articles, newsletters, or social media. It helps them produce engaging content by highlighting popular repositories and trends, keeping their audience informed about the latest developments in AI.
Educators and training institutions employ this skill to curate relevant AI projects for courses, workshops, or hackathons. It allows them to showcase real-world examples and trending tools, enhancing learning materials and keeping students engaged with current industry practices in AI and machine learning.
Offer a free tier with basic GitHub trend fetching and a paid tier with advanced features like custom filters, historical data, and higher rate limits. Revenue is generated through subscription plans for businesses and developers needing detailed analytics, with potential upsells for API access and integration support.
Integrate this skill into a larger analytics platform targeting enterprises, providing insights into AI project trends for competitive analysis and market research. Revenue comes from licensing fees, custom dashboard development, and consulting services for companies looking to leverage GitHub data for strategic decisions.
Monetize by promoting AI tools, courses, or cloud services related to trending GitHub projects through affiliate links or partnerships. Revenue is generated from commissions on referrals, with additional income from sponsored content or featured listings in the leaderboard reports for relevant products and services.
π¬ Integration Tip
Set the GITHUB_TOKEN environment variable to avoid rate limits and ensure reliable data fetching for consistent performance in automated workflows.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Query the DeepWiki MCP server for GitHub repository documentation, wiki structure, and AI-powered questions.
Automated GitHub PR code review with diff analysis, lint integration, and structured reports. Use when reviewing pull requests, checking for security issues,...
Essential Git commands and workflows for version control, branching, and collaboration.
Advanced git operations beyond add/commit/push. Use when rebasing, bisecting bugs, using worktrees for parallel development, recovering with reflog, managing subtrees/submodules, resolving merge conflicts, cherry-picking across branches, or working with monorepos.
Format commit messages using the Conventional Commits specification. Use when creating commits, writing commit messages, or when the user mentions commits, git commits, or commit messages. Ensures commits follow the standard format for automated tooling, changelog generation, and semantic versioning.