YouTube Shorts Hook Analyzer

YouTube

Operated by Sourcelane✓ verified

A video analysis connector for YouTube Shorts and short-form videos that extracts structured metadata for content analysis and creative iteration: identifies the exact opening hook (spoken, on-screen, or both), classifies hook type (e.g., bold claim, curiosity gap, question), measures hook timing and explains its persuasive function; captures every on-screen text overlay with timestamps and reading order (including burned‑in captions); isolates calls-to-action with timestamps; breaks the video into labeled segments/beats with one-line summaries; computes pacing and editing metrics such as scene/cut count and cuts-per-minute; generates a full verbatim transcript of spoken audio; detects format signals (talking‑head vs. other formats, voiceover, music, burned‑in captions); and assigns topical and content‑type classifications (educational, entertainment, product promo, etc.). Outputs are structured, timestamped annotations and analysis designed for content research, creative benchmarking, and automated text/ML pipelines.

Verified Sep 28, 12:11 AM

$0.15

per video

Up to 6 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Study top-performing creators or competitors to reverse-engineer hook formulas and CTA phrasing
Build a swipe file of proven hook types, on-screen text examples, and CTA wording for scriptwriting
Quality‑assure short-form videos by checking hook timing, caption pacing, and segment structure before publishing
Convert short-form video content into structured annotations for ingestion into LLMs, content analysis, or ML training

Trust & reliability

7d uptime trend

Window	Uptime	Success rate	p50	p95
24h	—	—	—	—
7d	—	—	—	—
30d	—	—	—	—

Calling contract

Call it through Sourcelane's gateway or MCP server. We run the connector, apply your agent's spend guardrails, and bill only the results returned.

Call it via Sourcelane

curl -X POST https://cool-puffin-608.convex.site/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"youtube-shorts-hook-analyzer","params":{"videoUrls":["https://www.youtube.com/shorts/f7y2XikE7sY"]},"maxResults":10}'

Request params

Field	Type	Required	Description
`videoUrls`	array	required	One YouTube Shorts (or regular video) URL per line.
`language`	string	optional	ISO 639-1 code (e.g. 'en', 'es') to hint the spoken language for transcription. Leave as 'auto' to auto-detect.
`includeTranscript`	boolean	optional	Include the full verbatim spoken transcript in the output. Turn off to keep records smaller if you only need the hook and on-screen text.
`maxDurationSeconds`	integer	optional	Skip videos longer than this. Set 0 for no limit.

Each result contains

Field	Type	Description
`inputUrl`	string	Input Url
`videoId`	string	Video Id
`title`	string	Title
`channelName`	string	Channel Name
`channelUrl`	string	Channel Url
`publishedAt`	string	Published At
`durationSeconds`	integer	Duration Seconds
`viewCount`	integer	View Count
`likeCount`	integer	Like Count
`commentCount`	integer	Comment Count
`language`	string	Language
`hookText`	string	Hook Text
`hookDeliveredAs`	string	—
`hookType`	string	—
`hookDurationSeconds`	number	—
`hookAnalysis`	string	—
`onScreenText`	array	—
`onScreenTextCombined`	string	—
`transcript`	string	—
`ctas`	array	—
`ctaCount`	integer	—
`structure`	array	—
`sceneChanges`	integer	—
`cutsPerMinute`	number	—
`hasVoiceover`	boolean	—
`hasMusic`	boolean	—
`hasBurnedInCaptions`	boolean	—
`isTalkingHead`	boolean	—
`contentType`	string	—
`topics`	array	—

Use YouTube Shorts Hook Analyzer from Claude, ChatGPT or Cursor

Pick your tool and connect in under a minute. Then just ask — for example: “Get the transcript of this video and turn it into a blog outline: <url>”

Connect Claude

Web, desktop and mobile. Paste one URL.

1Copy your personal connector URL
2In Claude open Settings → Connectors → Add custom connector
3Paste the URL and click Add — done

Manual setup (config files, REST, Python) +

Claude Code

Adds the Sourcelane MCP server with your key as a header.

terminal

claude mcp add --transport http sourcelane https://cool-puffin-608.convex.site/mcp \
  --header "Authorization: Bearer sl_live_your_agent_key"

Claude Desktop (config file)

Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.

claude_desktop_config.json

{
  "mcpServers": {
    "sourcelane": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://cool-puffin-608.convex.site/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

Cursor & Windsurf

Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).

mcp.json

{
  "mcpServers": {
    "sourcelane": {
      "url": "https://cool-puffin-608.convex.site/mcp",
      "headers": {
        "Authorization": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

VS Code

Save as .vscode/mcp.json. VS Code prompts for your key once.

.vscode/mcp.json

{
  "servers": {
    "sourcelane": {
      "type": "http",
      "url": "https://cool-puffin-608.convex.site/mcp",
      "headers": {
        "Authorization": "Bearer ${input:sourcelane-key}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "sourcelane-key",
      "description": "Sourcelane agent key",
      "password": true
    }
  ]
}

ChatGPT Custom GPT (Actions)

Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.

OpenAPI schema URL

https://sourcelane-amber.vercel.app/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://cool-puffin-608.convex.site/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"youtube-shorts-hook-analyzer","params":{"videoUrls":["https://www.youtube.com/shorts/f7y2XikE7sY"]},"maxResults":10}'

Python, LangChain, CrewAI, OpenAI Agents SDK…

Wrap the REST call as a tool, or point an MCP client at the endpoint.

python

import requests

res = requests.post(
    "https://cool-puffin-608.convex.site/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "youtube-shorts-hook-analyzer",
        "params": {"videoUrls":["https://www.youtube.com/shorts/f7y2XikE7sY"]},
        "maxResults": 10,
    },
    timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])

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