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Processes audio, images, videos, and PDFs, and generates images/videos using Google Gemini, Imagen, and Veo models. Useful for transcription, OCR, visual Q&A, document extraction, and media generation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/bmad-skills:ai-multimodalThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Process audio, images, videos, documents, and generate images/videos using Google Gemini's multimodal API.
references/audio-processing.mdreferences/image-generation.mdreferences/video-analysis.mdreferences/video-generation.mdreferences/vision-understanding.mdscripts/check_setup.pyscripts/document_converter.pyscripts/gemini_batch_process.pyscripts/media_optimizer.pyscripts/requirements.txtscripts/tests/requirements.txtscripts/tests/test_document_converter.pyscripts/tests/test_gemini_batch_process.pyscripts/tests/test_media_optimizer.pyProcess audio, images, videos, documents, and generate images/videos using Google Gemini's multimodal API.
export GEMINI_API_KEY="your-key" # Get from https://aistudio.google.com/apikey
pip install google-genai python-dotenv pillow
Verify setup: python scripts/check_setup.py
Analyze media: python scripts/gemini_batch_process.py --files <file> --task <analyze|transcribe|extract>
gemini command is available, then use "<prompt to analyze image>" | gemini -y -m gemini-2.5-flash command. If gemini command is not available, use python scripts/gemini_batch_process.py --files <file> --task analyze command.
Generate content: python scripts/gemini_batch_process.py --task <generate|generate-video> --prompt "description"Stdin support: You can pipe files directly via stdin (auto-detects PNG/JPG/PDF/WAV/MP3).
cat image.png | python scripts/gemini_batch_process.py --task analyze --prompt "Describe this"python scripts/gemini_batch_process.py --files image.png --task analyze(traditional)
imagen-4.0-generate-001 (standard), imagen-4.0-ultra-generate-001 (quality), imagen-4.0-fast-generate-001 (speed)veo-3.1-generate-preview (8s clips with audio)gemini-2.5-flash (recommended), gemini-2.5-pro (advanced)gemini_batch_process.py: CLI orchestrator for transcribe|analyze|extract|generate|generate-video that auto-resolves API keys, picks sensible default models per task, streams files inline vs File API, and saves structured outputs (text/JSON/CSV/markdown plus generated assets) for Imagen 4 + Veo workflows.media_optimizer.py: ffmpeg/Pillow-based preflight tool that compresses/resizes/converts audio, image, and video inputs, enforces target sizes/bitrates, splits long clips into hour chunks, and batch-processes directories so media stays within Gemini limits.document_converter.py: Gemini-powered converter that uploads PDFs/images/Office docs, applies a markdown-preserving prompt, batches multiple files, auto-names outputs under docs/assets, and exposes CLI flags for model, prompt, auto-file naming, and verbose logging.check_setup.py: Interactive readiness checker that verifies directory layout, centralized env resolver, required Python deps, and GEMINI_API_KEY availability/format, then performs a live Gemini API call and prints remediation instructions if anything fails.Use --help for options.
Load for detailed guidance:
| Topic | File | Description |
|---|---|---|
| Audio | references/audio-processing.md | Audio formats and limits, transcription (timestamps, speakers, segments), non-speech analysis, File API vs inline input, TTS models, best practices, cost and token math, and concrete meeting/podcast/interview recipes. |
| Images | references/vision-understanding.md | Vision capabilities overview, supported formats and models, captioning/classification/VQA, detection and segmentation, OCR and document reading, multi-image workflows, structured JSON output, token costs, best practices, and common product/screenshot/chart/scene use cases. |
| Image Gen | references/image-generation.md | Imagen 4 and Gemini image model overview, generate_images vs generate_content APIs, aspect ratios and costs, text/image/both modalities, editing and composition, style and quality control, safety settings, best practices, troubleshooting, and common marketing/concept-art/UI scenarios. |
| Video | references/video-analysis.md | Video analysis capabilities and supported formats, model/context choices, local/inline/YouTube inputs, clipping and FPS control, multi-video comparison, temporal Q&A and scene detection, transcription with visual context, token and cost guidance, and optimization/best-practice patterns. |
| Video Gen | references/video-generation.md | Veo model matrix, text-to-video and image-to-video quick start, multi-reference and extension flows, camera and timing control, configuration (resolution, aspect, audio, safety), prompt design patterns, performance tips, limitations, troubleshooting, and cost estimates. |
Formats: Audio (WAV/MP3/AAC, 9.5h), Images (PNG/JPEG/WEBP, 3.6k), Video (MP4/MOV, 6h), PDF (1k pages) Size: 20MB inline, 2GB File API
npx claudepluginhub bmad-labs/skills --plugin bmad-skillsProvides patterns for multimodal LLM integration: vision (image analysis, document understanding), audio (STT, TTS), video generation (Kling, Sora, Veo, Runway). Use for AI pipelines with images, audio, video.
Analyzes PDFs, images, videos, YouTube links, and documents using Google Gemini. Generates images from text prompts with Nano Banana Pro.
Orchestrates Google Vertex AI multimodal operations: video analysis with Gemini 2.5, image generation with Imagen 4, audio with Lyria, and marketing campaign automation via Python SDK.