gr

Get workflow advice — which /gr command best fits your task

Analyze any content — URL, file, or pasted text

Diagnose /gr plugin setup, MCP wiring, and API connectivity

Check status of explainer video projects

Bridge workflow — analyze content with Gemini research tools, then synthesize an explainer video

Full explainer video workflow — setup, inject content, generate pipeline, review, render

First-time setup guide — verify config, discover commands, and run your first tool

Manually add knowledge to the Weaviate store

View and change Gemini model preset

Search and browse past research, video notes, and analyses

Launch Gemini Deep Research Agent with interview-driven brief

Deep document research with evidence tiers and cross-referencing

Deep research on any topic with evidence-tier labeling

Web search via Gemini grounding

Query, debug, and evaluate MLflow traces from Gemini tool calls

Multi-turn video Q&A session

Analyze a video (YouTube URL, local file, or directory)

Fetch YouTube video comments and analyze them via Gemini Flash for sentiment and key opinions (runs in background)

Bridge agent that combines Gemini research analysis with video synthesis. Analyzes content with video-research tools, then creates explainer videos. Use when converting research, videos, or articles into explainer content.

Expert workflow advisor for the /gr plugin. Recommends the optimal command and workflow for research, video analysis, content extraction, or knowledge management tasks. Checks prior work first.

Multi-phase research specialist that chains Gemini research tools for comprehensive topic analysis. Use when you need thorough investigation with evidence tiers, source verification, and orchestrated research workflows.

Video analysis specialist that extracts comprehensive insights from YouTube videos. Use for detailed breakdowns, command extraction, workflow analysis, and iterative video Q&A sessions.

Full pipeline orchestrator for explainer videos. Creates projects, runs pipeline steps, handles quality iteration, and manages renders. Use when you need to produce a complete explainer video.

Generate interactive HTML visualization from analysis data and capture screenshot (runs in background after main analysis completes)

Generates interactive HTML visualizations (concept maps, evidence networks, knowledge graphs) from Gemini analysis results. Triggers automatically after /gr:video, /gr:research, /gr:analyze.

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.

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.

Use when working with MLflow traces: debugging via MCP tools, analyzing performance, logging feedback, writing custom scorers/evaluations, or cleaning up trace data

Builds precise research briefs through adversarial user interviews

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.

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.

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.

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.

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.

FFmpeg video/audio processing — conversion, scaling, compression, trimming, concatenation, AI post-processing. Not for audio ducking/voice mixing (tts-production) or Remotion rendering.