Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Process audio, images, videos, documents, and generate images using Google Gemini's multimodal API. Unified interface for all multimedia content understanding and generation.
| Task | Audio | Image | Video | Document | Generation |
|---|---|---|---|---|---|
| Transcription | ✓ | - | ✓ | - | - |
| Summarization | ✓ | ✓ | ✓ | ✓ | - |
| Q&A | ✓ | ✓ | ✓ | ✓ | - |
| Object Detection | - | ✓ | ✓ | - | - |
| Text Extraction | - | ✓ | - | ✓ | - |
| Structured Output | ✓ | ✓ | ✓ | ✓ | - |
| Creation | TTS | - | - | - | ✓ |
| Timestamps | ✓ | - | ✓ | - | - |
| Segmentation | - | ✓ | - | - | - |
API Key Setup: Supports both Google AI Studio and Vertex AI.
The skill checks for GEMINI_API_KEY in this order:
export GEMINI_API_KEY="your-key".env.claude/.env.claude/skills/.env.claude/skills/ai-multimodal/.envGet API key: https://aistudio.google.com/apikey
For Vertex AI:
export GEMINI_USE_VERTEX=true
export VERTEX_PROJECT_ID=your-gcp-project-id
export VERTEX_LOCATION=us-central1 # Optional
Install SDK:
pip install google-genai python-dotenv pillow
Transcribe Audio:
python scripts/gemini_batch_process.py \
--files audio.mp3 \
--task transcribe \
--model gemini-2.5-flash
Analyze Image:
python scripts/gemini_batch_process.py \
--files image.jpg \
--task analyze \
--prompt "Describe this image" \
--output docs/assets/<output-name>.md \
--model gemini-2.5-flash
Process Video:
python scripts/gemini_batch_process.py \
--files video.mp4 \
--task analyze \
--prompt "Summarize key points with timestamps" \
--output docs/assets/<output-name>.md \
--model gemini-2.5-flash
Extract from PDF:
python scripts/gemini_batch_process.py \
--files document.pdf \
--task extract \
--prompt "Extract table data as JSON" \
--output docs/assets/<output-name>.md \
--format json
Generate Image:
python scripts/gemini_batch_process.py \
--task generate \
--prompt "A futuristic city at sunset" \
--output docs/assets/<output-file-name> \
--model gemini-2.5-flash-image \
--aspect-ratio 16:9
Optimize Media:
# Prepare large video for processing
python scripts/media_optimizer.py \
--input large-video.mp4 \
--output docs/assets/<output-file-name> \
--target-size 100MB
# Batch optimize multiple files
python scripts/media_optimizer.py \
--input-dir ./videos \
--output-dir docs/assets/optimized \
--quality 85
Convert Documents to Markdown:
# Convert to PDF
python scripts/document_converter.py \
--input document.docx \
--output docs/assets/document.md
# Extract pages
python scripts/document_converter.py \
--input large.pdf \
--output docs/assets/chapter1.md \
--pages 1-20
For detailed implementation guidance, see:
references/audio-processing.md - Transcription, analysis, TTS
references/vision-understanding.md - Captioning, detection, OCR
references/video-analysis.md - Scene detection, temporal understanding
references/document-extraction.md - PDF processing, structured output
references/image-generation.md - Text-to-image, editing
Input Pricing:
Token Rates:
TTS Pricing:
gemini-2.5-flash for most tasks (best price/performance)media_optimizer.py)Free Tier:
YouTube Limits:
Storage Limits:
Common errors and solutions:
All scripts support unified API key detection and error handling:
gemini_batch_process.py: Batch process multiple media files
media_optimizer.py: Prepare media for Gemini API
document_converter.py: Convert documents to PDF
Run any script with --help for detailed usage.
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.
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This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
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Unified analysis pipeline for affinity-based proteomics platforms — Olink (PEA, NPX) and SomaLogic SomaScan (SOMAmer, RFU). Platform-aware QC, normalisation, differential abundance, volcano plots, heatmaps, and PCA.
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