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› mrgoonie/claudekit-skills
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ai-multimodal
GitHub基于 Google Gemini API 的多模态处理技能，涵盖音视频分析、图像理解与生成、文档提取及结构化数据输出。支持长上下文窗口和多模型选择，适用于多媒体内容理解与生成任务。
Trigger Scenarios
需要转录音频或视频并获取时间戳
对图片进行 OCR、物体检测或视觉问答
从 PDF 等文档中提取表格和图表数据
根据文本提示生成或编辑图像
Install
npx skills add mrgoonie/claudekit-skills --skill ai-multimodal -g -y
SKILL.md
Frontmatter
{
"name": "ai-multimodal",
"license": "MIT",
"description": "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.",
"allowed-tools": [
"Bash",
"Read",
"Write",
"Edit"
]
}
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
Version History
- 80113d8 Current 2026-08-20 08:13
