ai-multimodal

Q: How do I install ai-multimodal?

Run npx skills add https://github.com/samhvw8/dot-claude --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).

by samhvw8Media & Creative

Multimodal AI processing via Google Gemini API (2M tokens context). Capabilities: audio (transcription, 9.5hr max, summarization, music analysis), images (captioning, OCR, object detection, segmentation, visual Q&A), video (scene detection, 6hr max, YouTube URLs, temporal analysis), documents (PDF extraction, tables, forms, charts), image generation (text-to-image, editing). Actions: transcribe, analyze, extract, caption, detect, segment, generate from media. Keywords: Gemini API, audio transcription, image captioning, OCR, object detection, video analysis, PDF extraction, text-to-image, multimodal, speech recognition, visual Q&A, scene detection, YouTube transcription, table extraction, form processing, image generation, Imagen. Use when: transcribing audio/video, analyzing images/screenshots, extracting data from PDFs, processing YouTube videos, generating images from text, implementing multimodal AI features.

Installs: 61
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Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/samhvw8/dot-claude --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

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-flash for 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?

How do I install ai-multimodal?

Run npx skills add https://github.com/samhvw8/dot-claude --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 samhvw8 in samhvw8/dot-claude. It has 61 recorded installs.

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