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video-research-mcp
video-research-mcp contient 11 skills collectées depuis Galbaz1, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Produces voiceover audio via ElevenLabs TTS API. Activates for TTS generation, voice tuning, audio ducking, or multilingual narration — not for voice AI agents, transcription, or music.
Generate AI video with Veo or Sora. Triggers on text-to-video, image-to-video, video extension, style-consistent generation. Not for video analysis, research, or FFmpeg editing.
Orchestrate multi-clip AI video projects — style anchors, chaining patterns, frame-level QA, montage assembly. Not for video analysis, research, provider settings, or FFmpeg encoding.
FFmpeg video/audio processing — conversion, scaling, compression, trimming, concatenation, AI post-processing. Not for audio ducking/voice mixing (tts-production) or Remotion rendering.
Enhances image generation prompts with Subject-Context-Style structure, style anchors, character consistency, mcp-image workflows. Not for video generation, TTS, FFmpeg, audio, or design-to-code.
Interactive onboarding for the Weaviate knowledge store. Guides users through choosing a deployment type (Cloud, Local Docker, or Custom), setting environment variables, and verifying the connection. Activates when users want to set up or configure Weaviate for persistent knowledge storage.
Recommends the optimal /gr command when the user asks about Gemini-powered research, YouTube video analysis, web content extraction, or Weaviate knowledge queries. Activates only when the request matches /gr plugin capabilities and no specific /gr command was already chosen — not for code editing, debugging, testing, git operations, or general questions.
Teaches Claude how to effectively use the 28 video-research-mcp tools. Activates when working with video analysis, deep research, content extraction, web search, or knowledge store via the video-research MCP server.
Teaches Claude how to use the 15 video explainer tools to create explainer videos from research content. Activates when working with video synthesis, explainer creation, or the video-explainer MCP server.
Use when working with MLflow traces: debugging via MCP tools, analyzing performance, logging feedback, writing custom scorers/evaluations, or cleaning up trace data
Generates interactive HTML visualizations (concept maps, evidence networks, knowledge graphs) from Gemini analysis results. Triggers automatically after /gr:video, /gr:research, /gr:analyze.