Sift Web Tools: YouTube Thumbnail Critique & Scorer is a paid API for AI agents from sift.srv1996466.hstgr.cloud, paid per call via x402, $0.015/call, status unknown (last checked 2026-10-20).
Analyzes a YouTube thumbnail image URL and returns a 0-100 quality score with readability, contrast, text, clickbait risk, focal point, face/emotion detection, and concrete fix suggestions.
Thumbnail critique: score 0-100, readability at feed size, text, contrast, clickbait risk, fixes. Looks at a thumbnail image URL (jpeg, png or webp, up to 4 MB) the way a viewer sees it at feed size and returns a 0-100 score, whether it reads when small, the exact text in it, contrast, focal point, face and emotion, clickbait risk, strengths and concrete fixes. Pass the video title to check title and thumbnail work together.
Returns a JSON object with: a 0-100 quality score, a verdict string, a boolean for readability at small/feed size, the exact text detected in the image, a contrast rating (e.g. 'ok', 'poor', 'strong'), clickbait risk level (e.g. 'low', 'medium', 'high'), and an array of concrete fix suggestions.
GEThttps://sift.srv1996466.hstgr.cloud/v1/yt/thumbnail-check?utm_source=zero.xyzUse this endpoint when you need a structured, AI-powered critique of a YouTube thumbnail image specifically — covering visual readability at feed size, text density, contrast, clickbait risk, and actionable fixes in a single call. Prefer this over generic image-analysis APIs when you want thumbnail-specific scoring (0-100) and YouTube-context feedback, and especially when you want to optionally cross-check title/thumbnail coherence.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"fixes": [
"Cut the text to 3 words"
],
"score": 62,
"verdict": "Clear focal point but too much text",
"contrast": "ok",
"clickbait_risk": "low",
"readable_at_small_size": false
}
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