# Summarize a YouTube video with timestamps

**Use case:** 

Paste a YouTube link and get a 5-bullet summary with timestamps and quotes. No API keys needed. You set the fidelity. By default it reads the captions and thumbnail for a few cents. Ask about what's on screen, or set Frames to extract, and it downloads the video and reads up to 12 frames (videos up to 10 minutes, about $0.20). Pick a stronger model, such as Claude Opus 5.5, for more detail.

## Input

```json
{
  "video": "https://www.youtube.com/watch?v=_f5VEaR-F2k",
  "prompt": "Summarize this video in 5 bullets. For each bullet, include a rough timestamp (e.g. 0:42) and quote any spoken line that matters.",
  "llmProvider": "anthropic",
  "model": "default",
  "skipDestination": true,
  "writeBehavior": "auto",
  "framesToExtract": 0,
  "allowLongVideos": false,
  "forceFreshRun": false,
  "maxChargeUsd": 0
}
```

## Output

```json
{
  "completionTimestamp": {
    "label": "Completed",
    "format": "date"
  },
  "sourceUrl": {
    "label": "Source",
    "format": "link"
  },
  "status": {
    "label": "Status",
    "format": "text"
  },
  "analysisMode": {
    "label": "How it watched",
    "format": "text"
  },
  "estimatedCostUsd": {
    "label": "Est. $",
    "format": "number"
  },
  "analysisFull": {
    "label": "Analysis",
    "format": "text"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Video → LLM Analyzer Actor is ready to run with the inputs already set for "Summarize a YouTube video with timestamps". [Sign up or log in](https://console.apify.com/create-task-from-example/LdgIzPwMcQWiBbcF2) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Summarize a YouTube video with timestamps" task

The Video → LLM Analyzer Actor will start running based on the input automatically. You can also change all the input fields, like video, what should the llm do with this video?, and more, to match your specific use case.

### 3. Receive the "Summarize a YouTube video with timestamps" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as completed, source, status, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Summarize a YouTube video with timestamps" task via API](https://apify.com/grizzlygriff/video-llm-analyzer.md).

## About this Actor

This example demonstrates how to use [Video → LLM Analyzer](https://apify.com/grizzlygriff/video-llm-analyzer.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/grizzlygriff/video-llm-analyzer.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/grizzlygriff/video-llm-analyzer.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).