# video-understanding

> video-understanding — bill492-video-understanding. Use this tool when you need to analyze and understand video content, leveraging Google Gemini's multimodal AI capabilities to extract insights and meaning from visual and audio data. It solves problems such as video classification, object detection, and scene understanding, providing outputs like tagged entities, transcripts, and summarized content. Ideal for use cases like content moderation, media analysis, and automated video indexing, where accurate video understanding is crucial.

Canonical page: https://skillsregistry.net/skills/bill492-video-understanding  
JSON: https://api.skillsregistry.net/v1/skills/bill492-video-understanding

## Description

Analyze videos with Google Gemini multimodal AI.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** media
- **Updated:** 2026-09-24

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/bill492-video-understanding)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "bill492-video-understanding"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/bill492-video-understanding` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/bill492-video-understanding/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt