القائمة
Search movies/TV, get cast, ratings, streaming info, and personalized recommendations via TMDb API.
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/duclm1x1/Dive-Ai --skill tmdbيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
استنادا إلى تصنيف SOC المهني
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
عرض SKILL.md
| name | tmdb |
| description | Search movies/TV, get cast, ratings, streaming info, and personalized recommendations via TMDb API. |
| homepage | https://www.themoviedb.org/ |
| metadata | {"clawdis":{"emoji":"🎬","requires":{"bins":["uv"],"env":["TMDB_API_KEY"]},"primaryEnv":"TMDB_API_KEY"}} |
Comprehensive movie and TV information with streaming availability, recommendations, and personalization.
Set environment variable:
TMDB_API_KEY: Your TMDb API key (free at themoviedb.org)# Search movies
uv run {baseDir}/scripts/tmdb.py search "Inception"
# Search TV shows
uv run {baseDir}/scripts/tmdb.py search "Breaking Bad" --tv
# Search people (actors, directors)
uv run {baseDir}/scripts/tmdb.py person "Christopher Nolan"
# Full movie info
uv run {baseDir}/scripts/tmdb.py movie 27205
# With cast
uv run {baseDir}/scripts/tmdb.py movie 27205 --cast
# TV show details
uv run {baseDir}/scripts/tmdb.py tv 1396
# By name (searches first, then shows details)
uv run {baseDir}/scripts/tmdb.py info "The Dark Knight"
# Find streaming availability
uv run {baseDir}/scripts/tmdb.py where "Inception"
uv run {baseDir}/scripts/tmdb.py where 27205
# Specify region
uv run {baseDir}/scripts/tmdb.py where "Inception" --region GB
# Trending this week
uv run {baseDir}/scripts/tmdb.py trending
uv run {baseDir}/scripts/tmdb.py trending --tv
# Recommendations based on a movie
uv run {baseDir}/scripts/tmdb.py recommend "Inception"
# Advanced discover
uv run {baseDir}/scripts/tmdb.py discover --genre action --year 2024
uv run {baseDir}/scripts/tmdb.py discover --genre sci-fi --rating 7.5
# Get personalized suggestions (uses Plex history + preferences)
uv run {baseDir}/scripts/tmdb.py suggest <user_id>
# Set preferences
uv run {baseDir}/scripts/tmdb.py pref <user_id> --genres "sci-fi,thriller,drama"
uv run {baseDir}/scripts/tmdb.py pref <user_id> --directors "Christopher Nolan,Denis Villeneuve"
uv run {baseDir}/scripts/tmdb.py pref <user_id> --avoid "horror,romance"
# View preferences
uv run {baseDir}/scripts/tmdb.py pref <user_id> --show
# Add to watchlist
uv run {baseDir}/scripts/tmdb.py watchlist <user_id> add 27205
uv run {baseDir}/scripts/tmdb.py watchlist <user_id> add "Dune: Part Two"
# View watchlist
uv run {baseDir}/scripts/tmdb.py watchlist <user_id>
# Remove from watchlist
uv run {baseDir}/scripts/tmdb.py watchlist <user_id> rm 27205
If the Plex skill is available, suggest command pulls recent watch history to inform recommendations.
If ppl skill is available, preferences are stored as notes on the user's contact for persistence across sessions.
Common genres for --genre filter: