Estimate the probability that a document's prose was written by AI, with the specific linguistic tells and an honest abstention when the document isn't prose. Uses the Stipple API (free anonymous tier).
Get the document. URL, local file path (PDF, DOCX, TXT, MD), or raw text via --text.
Run detection.
curl -X POST https://www.stipple.sh/v1/detect-ai-text \
-F "file=@essay.pdf" \
-H "Authorization: Bearer $STIPPLE_API_KEY"
For raw text: POST JSON {"text": "..."} to the same endpoint.
Interpret the response.
applicable: false — the document is not prose (forms, tables, scans, spreadsheets). Detection is deliberately refused rather than guessed. Report this and stop.probability — model confidence (0–1), NOT a calibrated truthlean — "ai" | "human" | "unsure"tells[] — the specific phrases/patterns flagged (e.g. "It is important to note that", uniform sentence length, low burstiness)reasoning — why the model reached its verdictlimitations — always present; the API states its own noise profileReport honestly. This measures style, not authenticity:
| Question | Tool |
|---|---|
| Was this written by AI? (style) | this skill |
| Is this document genuine/tampered? (forensics) | verify-document skill |
A human can write generically; an AI can write plainly. One triage signal, never a verdict.
AI-written probability: 0.87 (lean: ai)
prose ratio: 0.82
linguistic tells:
- "It is important to note that, in today's fast-paced world" (stock phrase)
- uniform sentence length across paragraphs
- low burstiness; no authorial asides
reasoning: The text relies entirely on formulaic transition clichés...
limitations: The probability is the model's CONFIDENCE, not a calibrated truth.
applicable: false — the engine refuses rather than guessing