
ai-multimodal
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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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/mrgoonie/claudekit-skills --skill ai-multimodal- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ai-multimodal automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
AI Multimodal Processing Skill
Process audio, images, videos, documents, and generate images using Google Gemini's multimodal API. Unified interface for all multimedia content understanding and generation.
Core Capabilities
Audio Processing
- Transcription with timestamps (up to 9.5 hours)
- Audio summarization and analysis
- Speech understanding and speaker identification
- Music and environmental sound analysis
- Text-to-speech generation with controllable voice
Image Understanding
- Image captioning and description
- Object detection with bounding boxes (2.0+)
- Pixel-level segmentation (2.5+)
- Visual question answering
- Multi-image comparison (up to 3,600 images)
- OCR and text extraction
Video Analysis
- Scene detection and summarization
- Video Q&A with temporal understanding
- Transcription with visual descriptions
- YouTube URL support
- Long video processing (up to 6 hours)
- Frame-level analysis
Document Extraction
- Native PDF vision processing (up to 1,000 pages)
- Table and form extraction
- Chart and diagram analysis
- Multi-page document understanding
- Structured data output (JSON schema)
- Format conversion (PDF to HTML/JSON)
Image Generation
- Text-to-image generation
- Image editing and modification
- Multi-image composition (up to 3 images)
- Iterative refinement
- Multiple aspect ratios (1:1, 16:9, 9:16, 4:3, 3:4)
- Controllable style and quality
Capability Matrix
| Task | Audio | Image | Video | Document | Generation |
|---|---|---|---|---|---|
| Transcription | ✓ | - | ✓ | - | - |
| Summarization | ✓ | ✓ | ✓ | ✓ | - |
| Q&A | ✓ | ✓ | ✓ | ✓ | - |
| Object Detection | - | ✓ | ✓ | - | - |
| Text Extraction | - | ✓ | - | ✓ | - |
| Structured Output | ✓ | ✓ | ✓ | ✓ | - |
| Creation | TTS | - | - | - | ✓ |
| Timestamps | ✓ | - | ✓ | - | - |
| Segmentation | - | ✓ | - | - | - |
Model Selection Guide
Gemini 2.5 Series (Recommended)
- gemini-2.5-pro: Highest quality, all features, 1M-2M context
- gemini-2.5-flash: Best balance, all features, 1M-2M context
- gemini-2.5-flash-lite: Lightweight, segmentation support
- gemini-2.5-flash-image: Image generation only
Gemini 2.0 Series
- gemini-2.0-flash: Fast processing, object detection
- gemini-2.0-flash-lite: Lightweight option
Feature Requirements
- Segmentation: Requires 2.5+ models
- Object Detection: Requires 2.0+ models
- Multi-video: Requires 2.5+ models
- Image Generation: Requires flash-image model
Context Windows
- 2M tokens: ~6 hours video (low-res) or ~2 hours (default)
- 1M tokens: ~3 hours video (low-res) or ~1 hour (default)
- Audio: 32 tokens/second (1 min = 1,920 tokens)
- PDF: 258 tokens/page (fixed)
- Image: 258-1,548 tokens based on size
Quick Start
Prerequisites
API Key Setup: Supports both Google AI Studio and Vertex AI.
The skill checks for GEMINI_API_KEY in this order:
- Process environment:
export GEMINI_API_KEY="your-key" - Project root:
.env .claude/.env.claude/skills/.env.claude/skills/ai-multimodal/.env
Get 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
Common Patterns
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
Supported Formats
Audio
- WAV, MP3, AAC, FLAC, OGG Vorbis, AIFF
- Max 9.5 hours per request
- Auto-downsampled to 16 Kbps mono
Images
- PNG, JPEG, WEBP, HEIC, HEIF
- Max 3,600 images per request
- Resolution: ≤384px = 258 tokens, larger = tiled
Video
- MP4, MPEG, MOV, AVI, FLV, MPG, WebM, WMV, 3GPP
- Max 6 hours (low-res) or 2 hours (default)
- YouTube URLs supported (public only)
Documents
- PDF only for vision processing
- Max 1,000 pages
- TXT, HTML, Markdown supported (text-only)
Size Limits
- Inline: <20MB total request
- File API: 2GB per file, 20GB project quota
- Retention: 48 hours auto-delete
Reference Navigation
For detailed implementation guidance, see:
Audio Processing
references/audio-processing.md- Transcription, analysis, TTS- Timestamp handling and segment analysis
- Multi-speaker identification
- Non-speech audio analysis
- Text-to-speech generation
Image Understanding
references/vision-understanding.md- Captioning, detection, OCR- Object detection and localization
- Pixel-level segmentation
- Visual question answering
- Multi-image comparison
Video Analysis
references/video-analysis.md- Scene detection, temporal understanding- YouTube URL processing
- Timestamp-based queries
- Video clipping and FPS control
- Long video optimization
Document Extraction
references/document-extraction.md- PDF processing, structured output- Table and form extraction
- Chart and diagram analysis
- JSON schema validation
- Multi-page handling
Image Generation
references/image-generation.md- Text-to-image, editing- Prompt engineering strategies
- Image editing and composition
- Aspect ratio selection
- Safety settings
Cost Optimization
Token Costs
Input Pricing:
- Gemini 2.5 Flash: $1.00/1M input, $0.10/1M output
- Gemini 2.5 Pro: $3.00/1M input, $12.00/1M output
- Gemini 1.5 Flash: $0.70/1M input, $0.175/1M output
Token Rates:
- Audio: 32 tokens/second (1 min = 1,920 tokens)
- Video: ~300 tokens/second (default) or ~100 (low-res)
- PDF: 258 tokens/page (fixed)
- Image: 258-1,548 tokens based on size
TTS Pricing:
- Flash TTS: $10/1M tokens
- Pro TTS: $20/1M tokens
Best Practices
- Use
gemini-2.5-flashfor most tasks (best price/performance) - Use File API for files >20MB or repeated queries
- Optimize media before upload (see
media_optimizer.py) - Process specific segments instead of full videos
- Use lower FPS for static content
- Implement context caching for repeated queries
- Batch process multiple files in parallel
Rate Limits
Free Tier:
- 10-15 RPM (requests per minute)
- 1M-4M TPM (tokens per minute)
- 1,500 RPD (requests per day)
YouTube Limits:
- Free tier: 8 hours/day
- Paid tier: No length limits
- Public videos only
Storage Limits:
- 20GB per project
- 2GB per file
- 48-hour retention
Error Handling
Common errors and solutions:
- 400: Invalid format/size - validate before upload
- 401: Invalid API key - check configuration
- 403: Permission denied - verify API key restrictions
- 404: File not found - ensure file uploaded and active
- 429: Rate limit exceeded - implement exponential backoff
- 500: Server error - retry with backoff
Scripts Overview
All scripts support unified API key detection and error handling:
gemini_batch_process.py: Batch process multiple media files
- Supports all modalities (audio, image, video, PDF)
- Progress tracking and error recovery
- Output formats: JSON, Markdown, CSV
- Rate limiting and retry logic
- Dry-run mode
media_optimizer.py: Prepare media for Gemini API
- Compress videos/audio for size limits
- Resize images appropriately
- Split long videos into chunks
- Format conversion
- Quality vs size optimization
document_converter.py: Convert documents to PDF
- Convert DOCX, XLSX, PPTX to PDF
- Extract page ranges
- Optimize PDFs for Gemini
- Extract images from PDFs
- Batch conversion support
Run any script with --help for detailed usage.
Resources
FAQ
What does the ai-multimodal skill do?
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.
How do I install ai-multimodal?
Run npx skills add https://github.com/mrgoonie/claudekit-skills --skill ai-multimodal in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ai-multimodal/ (personal) or .claude/skills/ai-multimodal/ (project).
Which AI agents can use ai-multimodal?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ai-multimodal safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ai-multimodal?
It is published by mrgoonie in mrgoonie/claudekit-skills. It has 530 recorded installs.
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