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adamos486adamos486/skills/streaming-recommendations/skill.md

streaming-recommendations

Skill10 starsChanged 7 months agoMITView on GitHub

Recommends movies and TV shows to watch on streaming services. Gives 3-5 curated picks based on genre, mood, format, and streaming platform. Use when the user asks what to watch, wants streaming recommendations, or needs help picking a movie or show.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If any of the four dimensions are missing, ask one multiple-choice question at a time in this priority order.

    line 39
  2. Distinctive:

    If the user provides all four upfront (e.g., "recommend a funny movie on Netflix, something light"), skip straight to Step 3.

    line 72
  3. Distinctive:

    Search 2-3 queries to cross-reference availability and find quality picks.

    line 84
  4. Very specific:

    Use 🎬 for movies, 📺 for TV shows

    line 107

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
skill.md

Streaming Recommendations

Recommend 3-5 movies or TV shows to watch on streaming services, tailored to the user's genre, mood, format preference, and available platforms.

When to Use

  • User asks "what should I watch?"
  • User wants movie or TV show recommendations
  • User mentions streaming services and wants suggestions
  • User describes a mood or genre and wants entertainment picks

Process

Step 1: Parse the Request

Extract any preferences the user already provided. Look for these four dimensions:

DimensionExamples
FormatMovie, TV show, or either
GenreAction, comedy, sci-fi, drama, horror, thriller, documentary, animation, romance, fantasy, mystery, crime
Streaming serviceNetflix, Hulu, Disney+, HBO Max, Prime Video, Apple TV+, Peacock, Paramount+, Tubi, or "any"
Mood / vibeLight & fun, intense & gripping, thought-provoking, heartwarming, dark & gritty, nostalgic, suspenseful

Step 2: Ask What's Missing

If any of the four dimensions are missing, ask one multiple-choice question at a time in this priority order. Skip any dimension already provided:

  1. Format — "Are you in the mood for a movie or a TV show?"
    • Movie
    • TV show
    • Either is fine
  2. Genre — "What genre sounds good?"
    • Action / Adventure
    • Comedy
    • Drama
    • Sci-Fi / Fantasy
    • Horror / Thriller
    • Documentary
    • Surprise me
  3. Streaming service — "Which service are you watching on?"
    • Netflix
    • Hulu / Disney+
    • HBO Max
    • Prime Video
    • Apple TV+
    • Peacock / Paramount+
    • Any / I have them all
  4. Mood — "What vibe are you going for?"
    • Light & fun
    • Intense & gripping
    • Thought-provoking
    • Heartwarming
    • Dark & gritty
    • Surprise me

If the user provides all four upfront (e.g., "recommend a funny movie on Netflix, something light"), skip straight to Step 3.

"Surprise me" on genre or mood means pick freely — lean toward highly-rated or trending picks.

Step 3: Search for Recommendations

Always use web search to find current recommendations. Streaming catalogs change constantly — never rely solely on training data.

Build search queries combining the user's filters:

  • Example: "best light comedy movies on Netflix 2026"
  • Example: "top intense sci-fi TV shows on HBO Max 2026"

Search 2-3 queries to cross-reference availability and find quality picks. Prioritize:

  • Currently available on the specified service (verify availability)
  • Well-rated (IMDb 7.0+ or Rotten Tomatoes 75%+)
  • Mix of well-known and lesser-known titles for variety
  • Matches the stated mood/vibe, not just the genre

Step 4: Present as Rich Cards

Return 3-5 recommendations using this format for each:

### {emoji} Title (Year)
**Genre:** Genre1, Genre2 | **Rating:** Score (Source)
**Streaming on:** Service Name

Synopsis in 2-3 sentences. Spoiler-free. Written to sell the vibe, not just
summarize the plot. Make it compelling.

**Why you'll like it:** One sentence connecting this pick back to the user's
stated mood and preferences.

Formatting rules:

  • Use 🎬 for movies, 📺 for TV shows
  • Rating from IMDb (e.g., "8.2 IMDb") or Rotten Tomatoes (e.g., "94% RT") — whichever the search surfaces
  • Synopsis: 2-3 sentences, spoiler-free, emphasize tone and vibe over plot details
  • "Why you'll like it": Directly reference the user's mood or preferences — this is what makes it feel personal

Example Output

You asked for: An intense sci-fi TV show on Netflix

📺 3 Body Problem (2024)

Genre: Sci-Fi, Mystery | Rating: 7.7 IMDb Streaming on: Netflix

A mystery that spans decades and continents as a group of brilliant scientists confront the greatest threat in humanity's history. The stakes escalate relentlessly, blending real physics with jaw-dropping sci-fi concepts.

Why you'll like it: You wanted intense and gripping — this one doesn't let you breathe from the first episode.


📺 Silo (2023)

Genre: Sci-Fi, Drama | Rating: 8.0 IMDb Streaming on: Apple TV+

In a ruined and toxic future, thousands live in a giant underground silo. When the sheriff investigates what's outside, she uncovers shocking truths that could destroy the community.

Why you'll like it: Slow-burn intensity that builds and builds — perfect for that edge-of-your-seat craving.

Key Principles

  • Always search the web — streaming catalogs change; never guess availability
  • One question at a time — don't overwhelm with multiple questions
  • Personalize the "why" — tie every recommendation back to what the user asked for
  • Spoiler-free always — never reveal plot twists or endings
  • Variety matters — mix popular and under-the-radar picks
  • Verify availability — if unsure a title is on the stated service, say so
  • One and done — present the picks and let the user take it from there; don't prompt for follow-up

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