# video-watcher

> video-watcher — kartinw-video-watcher. Use this tool when you need to analyze video content by breaking it down into individual frames. It solves problems such as video summarization, object detection, and content moderation by extracting frames at regular intervals, providing a visual representation of the video's content. The tool takes a video file as input and outputs a series of image frames, making it useful for applications where video analysis is required.

Canonical page: https://skillsregistry.net/skills/kartinw-video-watcher  
JSON: https://api.skillsregistry.net/v1/skills/kartinw-video-watcher

## Description

Analyze video content by extracting frames at regular intervals.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## 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/kartinw-video-watcher)

## 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": "kartinw-video-watcher"
    }
  }
}
```

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