| name | ai-text-detector-github |
|---|---|
| description | Detect whether a passage shows AI-like writing signals and return an explainable risk estimate with confidence, caveats, and next steps. |
This skill wraps the local ai-detector-skill analyzer into a reusable open source Codex-style skill.
It is designed for:
- essays
- emails
- articles
- reviews
- forum posts
- other prose where a user asks whether the writing may be AI-generated
This skill returns a risk estimate, not proof of authorship.
Use this skill when:
- the user asks "is this AI-written?"
- the user asks to detect AI-generated text
- the user pastes a passage and asks whether it sounds machine-written
- the user wants a cautious AI-likeness review for a document or message
- Never present the score as proof.
- Never accuse a named person of cheating, fraud, or misconduct.
- Ask for a longer sample when the text is under about 80 words.
- Prefer "AI-like signals are present" over "This was written by AI".
- For high-stakes contexts, recommend human review and comparison with known writing samples.
- Receive the candidate text and check length.
- If the sample is under about 80 words, explain that the detector will be noisy and ask for a longer sample when possible.
- Save the text to a file or pipe it through stdin.
- Run the local detector:
ai-detect path/to/text.txt --jsonor:
python -m aidetect.cli path/to/text.txt --jsonor from the repository helper:
python scripts/detect.py path/to/text.txt --json- Parse the JSON result and validate that it includes:
scoreconfidenceverdictconclusionsignalscaveats
-
Respond in this order:
-
One-sentence conclusion with uncertainty.
-
Score and confidence.
-
Strongest evidence signals.
-
Caveats.
-
Next steps only when useful.
Good phrasing:
- "AI-like signals are present, but this is not proof."
- "The result is uncertain because the sample is short."
- "This should be reviewed against known writing samples."
Avoid:
- "This was definitely written by AI."
- "The detector proves misconduct."
- Any accusation against a named person.
SKILL.md: skill contract and usage rulesscripts/detect.py: repository-local wrapper for the detectorscripts/setup.sh: local environment bootstrapreferences/api-reference.md: response contract and CLI referenceassets/templates/report.md: reusable response template
- Keep the analyzer explainable and lightweight.
- Prefer local heuristics over hidden network calls.
- Update this file whenever behavior or output changes.