Best Practices on Recommendation Systems

:movie_camera: Python and OpenCV-based scene cut/transition detection program & library.

AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.

Cinemagoer is a Python package useful to retrieve and manage the data of the IMDb (to which we are not affiliated in any way) movie database about movies, people, characters and companies

A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.

A portable agent skill that makes AI agents research comparable projects, tradeoffs, costs, and failure conditions before giving build advice.

Research a US equity across fundamentals, valuation, technical context, peers, and current market data.

Test Cherry Studio PRs by resolving and checking out a PR, statically inspecting its changes, running interactive UI tests against a safely tracked Electron instance through CDP, producing a structured report, cleaning up only the owned test instance, and restoring the original branch.

A comprehensive monitoring, recommendation, and OpenAI-compatible gateway system for AI API endpoints with layered probing, health scoring, and self-hosted deployment.

Movie metadata scraper

Classic papers and resources on recommendation

Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username