Token导航 LogoToken导航TokenDH.com
前端设计敏感数据github未标认证来源可访问clear审计提醒

ai-multimodalAI 多式联运

Agent Skill

ai-multimodal 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

823

周安装

35

GitHub Stars

10

下载量

288
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ai-multimodal(AI 多式联运)
来源仓库:https://github.com/samhvw8/dot-claude
仓库路径:skills/ai-multimodal
安装命令:
npx skills add https://github.com/samhvw8/dot-claude --skill ai-multimodal
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/samhvw8/dot-claude --skill ai-multimodal

简介

ai-multimodal 处理多模态 AI 模型相关的协作与开发信息。

  • 适用于图像、文本、音频融合应用场景的设计参考。
  • 可集成于前端项目中对齐跨模态交互体验。
  • 注意不同模态间的同步延迟与用户体验平衡。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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

TaskAudioImageVideoDocumentGeneration
Transcription---
Summarization-
Q&A-
Object Detection---
Text Extraction---
Structured Output-
CreationTTS---
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:

  1. Process environment: export GEMINI_API_KEY="your-key"
  2. Project root: .env
  3. .claude/.env
  4. .claude/skills/.env
  5. .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

  1. Use gemini-2.5-flash for most tasks (best price/performance)
  2. Use File API for files >20MB or repeated queries
  3. Optimize media before upload (see media_optimizer.py)
  4. Process specific segments instead of full videos
  5. Use lower FPS for static content
  6. Implement context caching for repeated queries
  7. 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

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.2%
按下载量换算75

windsurf

22.91%
按下载量换算66

Antigravity

15.95%
按下载量换算46

trae

12.52%
按下载量换算36

OpenCode

8.58%
按下载量换算25

Gemini CLI

3.79%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

继续浏览同类 Skills