Anthropic Claude Watermark Checker
Anthropic Claude Watermark Checker takes pasted text or uploaded files and returns structured JSON on whether the writing is AI generated, with a focus on Claude-style copy. It uses a SynthID-Text-aware classifier and asks: Is this AI generated? The headline output field is isAiGenerated.
Claude’s text watermark is a version of Google DeepMind SynthID-Text, but it uses Anthropic’s own key. Anthropic has said a public detection API is coming; this Actor does not have that key. It is a classifier that still gives you structured JSON you can store, plus honest limitations on the row.
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What is Anthropic Claude Watermark Checker?
Paste a passage or upload a PDF / Word / text file. The Actor extracts text locally, sends a capped sample to the detector, and returns one dataset row per item: isAiGenerated, confidence, likely source, rationale, and billed token units.
No Claude login. Files are converted to text before the check so a large binary cannot be billed as extra tokens.
What can this Actor do?
- Check pasted text or uploaded files (PDF, DOCX, TXT, Markdown, HTML, JSON, CSV)
- Return
isAiGeneratedplus Claude-focused classifier fields in structured JSON - Sample long files from the start, middle, and end
- Cap characters per item so a huge upload cannot silently burn tokens
- Charge per check and per 1,000 input tokens of the sample
- Export JSON, CSV, or Excel, or pull results via the Apify API
Why screen text for Claude?
New Claude models (from August 2026) embed a SynthID-Text-style watermark, but you cannot read it without Anthropic’s key. Teams still need a repeatable JSON label for documents they already hold.
Typical jobs:
- Policy teams — log likely-Claude drafts while waiting for Anthropic’s detector API
- Admissions integrity — screen essays and personal statements
- Hiring take-homes — flag fully generated writeups
- Research labeling — tag corpora as likely Claude vs human
- Support QA — inspect long agent replies
- SEO review — catch undifferentiated generated articles
- Newsroom intake — label freelance copy
- Education tools — show confidence, not a red-card verdict
- Brand voice audits — find Claude-shaped pages
- Legal extras — attach a classifier score next to produced files
- Community moderation — sample long posts
- Internal audits — sample exported docs for Claude-heavy writing
How to use Anthropic Claude Watermark Checker
- Open the Actor in Apify Console
- Paste Text / Texts, or upload Files
- Keep Max characters per item at the default unless you know you need to send a longer sample
- Click Start
- Download the dataset or read it via the Apify API
Input example
{
"text": "Four score and seven years ago our fathers brought forth on this continent, a new nation...",
"texts": [
"In today's rapidly evolving digital landscape, it is important to note that leveraging synergistic paradigms..."
],
"files": ["https://example.com/memo.docx"],
"maxItems": 5,
"maxCharsPerItem": 24000
}| Field | Type | Default | Description |
|---|---|---|---|
text | string | — | One pasted passage |
texts | string[] | — | Extra pasted passages |
files | string[] | — | Uploaded file URLs (PDF, DOCX, or text) |
maxItems | integer | 5 | Cap on pasted samples + files this run |
maxCharsPerItem | integer | 24000 | Max characters sent to the detector per item (hard max 100,000) |
Output
Each dataset item is one check. The headline field is isAiGenerated. model is the detector family (synthid-text), not a specific chat model.
{
"id": "a1b2c3d4e5f67890",
"sourceType": "text",
"sourceName": "pasted-text-1",
"sourceUrl": null,
"textPreview": "Four score and seven years ago...",
"textLength": 312,
"wordCount": 58,
"truncated": false,
"isAiGenerated": false,
"watermarkDetected": null,
"watermarkType": null,
"matchesTargetProvider": false,
"likelySource": "human",
"likelihood": "low",
"confidence": 0.64,
"detectionMethod": "classifier",
"rationale": "Well-known human speech; no access to Anthropic's SynthID-Text key.",
"limitations": "Claude watermarks use Anthropic's key. This run is a writing-style classifier.",
"inputTokens": 940,
"outputTokens": 175,
"billedTokenUnits": 1,
"model": "synthid-text",
"targetProvider": "anthropic-claude",
"error": null,
"checkedAt": "2026-08-26T12:00:00.000Z"
}Pricing
Long files use more tokens than a tweet. This Actor passes that cost through with a margin.
| Event | When | Price (FREE) |
|---|---|---|
text-checked | Once per successful analysis | $0.005 |
input-1k-tokens | Per 1,000 input tokens of the sample actually sent (rounded up) | $0.001 |
| Actor start | Per run (× memory GB) | platform default |
Failed downloads are not billed.
Examples (excluding start fee):
- ~500-word paste (~800 tokens) → ≈ $0.006
- 24,000-character file sample → ≈ $0.012
Leave maxCharsPerItem at 24,000 unless you have a reason to send more.
Files and token safety
- Text is extracted locally. Images, audio, and zip archives are rejected.
- Files over 15 MB are rejected.
- Longer documents are sampled up to
maxCharsPerItem. - Short samples (under ~50 words) are weak evidence.
For a Google SynthID-Text check, use Google Gemini Watermark Checker. For ChatGPT images and audio (the media OpenAI actually watermarks), use OpenAI ChatGPT Watermark Checker.
Is it legal to check AI-generated text?
This Actor only analyzes content you provide. It does not log into Claude. Do not treat the score as legal proof of authorship. A Claude watermark answers “was Claude involved?”, not who the user was.
Tips
- Prefer longer passages — Anthropic notes watermark confidence rises with length
- Upload text-based PDFs, not scanned image-only pages
- Watch
billedTokenUnitsif a run costs more than you expected - Start with
maxItems1–3 while you learn the output shape
Image Credit
Image credit: Anthropic
