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gujincheng1128
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multimodal-looker

Analyze images, video, and audio via the MultiModalClient Python API.

Updated Mar 15, 2026
Search Tags:#analysis#multimodal#video#vision#audio#cross-modal#content-understanding
One-click install
npx skills add https://github.com/gujincheng1128/my-awesome-app --skill multimodal-looker-gujincheng1128
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: multimodal-looker
Source: https://github.com/gujincheng1128/my-awesome-app/tree/main/skills/multimodal-looker
Command: npx skills add https://github.com/gujincheng1128/my-awesome-app --skill multimodal-looker-gujincheng1128

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Multimodal-Looker provides a unified toolkit to analyze and understand content across images, videos, audio, and text, enabling deeper insights and faster decision-making.

Core Features & Use Cases

  • Content understanding: Deeply interpret multimedia content to produce descriptive and structured results.
  • Cross-modal retrieval: Enable searches of images or videos via natural language queries.
  • Content summarization: Generate concise summaries for long media.
  • Sentiment and entity analysis: Detect emotions, entities, and relationships within media and accompanying text.
  • Document and text comprehension: Extract information from text-heavy media and support Q&A

Quick Start

Analyze an image by URL to obtain a detailed description, text extraction, and object detection.

Frequently Asked Questions about multimodal-looker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform multimodal content analysis across images, video, and audio?▼

Multimodal content analysis across images, video, and audio is performed using a Python API client that processes media through dedicated endpoints to return structured results like descriptions and detected objects.

Can I use natural language queries for cross-modal search on video files?▼

Cross-modal search on video files is supported through natural language queries, allowing you to retrieve specific multimedia content by matching textual descriptions against visual and audio data.

How does cross-modal sentiment analysis work on multimedia content?▼

Cross-modal sentiment analysis detects emotions and entities within multimedia content and its accompanying text, mapping relationships across audio and visual signals to produce structured sentiment results.

Does the Python API client require external dependencies for video analysis?▼

The Python API client requires no external dependencies to execute video analysis, allowing direct integration to process video files and extract text, objects, and summaries.

What is the best way to generate summaries for long multimedia files?▼

Generating summaries for long multimedia files involves analyzing the unified media content to extract key information, producing concise text summaries from both visual and audio streams.

Can I analyze an image by URL to extract text and detect objects?▼

Analyzing an image by URL is supported to obtain detailed descriptions, text extraction, and object detection, returning structured results directly through the Python API client.

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