movies-for-ai-agents

First-run configuration for the movies-for-ai-agents plugin. Use when the user says "set up movies-for-ai-agents", "configure movies", "first run", "add my TMDB key", "set up my movie profile", or when any other movies-for-ai-agents skill calls an MCP tool that reports "TMDB API key not configured". Captures the TMDB API key and, optionally, a brief taste-priming pass (favorite genres, directors, a few favorite movies) so later recommendations work out of the gate.

Browse what's popular, trending, newly released, currently in theaters, or filter by IMDb rating / interest / director. Use when the user asks "what's popular right now", "what's trending", "what's new", "what's in theaters", "show me this week's movies", "anything good out lately", "sci-fi with IMDb 8+", "heist movies", "Nolan films", "hidden gems", or wants to see a feed of current hot titles. Not for personalized picks — for that, use `recommend`. Not for finding a specific title — for that, use `find-movie`.

Search for a specific movie by title, keyword, year, or fuzzy description. Use when the user asks "find that movie…", "what's the name of the movie where…", "search for [title]", "look up [title]", "tell me about [movie]", or wants information about a specific film they already have in mind. Not for open-ended recommendations — for that, use the `recommend` skill.

Silently keep the user's watched history and taste profile current as they mention movies in conversation. Use whenever the user says "I watched X", "I saw X last night", "I just finished X", "we watched X", "loved X", "hated X", "didn't like X", "that was great/terrible", "best movie ever", "worst movie", "add X to my watchlist", or otherwise signals a movie-viewing event or taste reaction — even if it's a passing mention in the middle of another topic. Do NOT trigger on hypotheticals ("I want to watch X", "I should watch X") — those belong on the watchlist instead. This skill exists so the user's taste profile and history stay rich without any manual logging.

Personalized movie recommendations tailored to the user's stored taste profile, watch history, and whatever mood/constraint they mention right now. Use when the user asks "what should I watch", "recommend me a movie", "suggest something", "I'm in the mood for [X]", "something like [X]", "help me pick a movie", "got two hours tonight — what should I watch", "anything I'd like that's new", or any other open-ended ask for a personalized pick. This is the flagship skill — invest in making each recommendation feel reasoned, not generic.