Ai Text Detector Github

AI Text Detector Skill

Overview

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.

Trigger Conditions

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

Required Behavior

• 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.

Execution Flow

1. Receive the candidate text and check length.
2. If the sample is under about 80 words, explain that the detector will be noisy and ask for a longer sample when possible.
3. Save the text to a file or pipe it through stdin.
4. Run the local detector:

bashCopy code
ai-detect path/to/text.txt --json

or:

bashCopy code
python -m aidetect.cli path/to/text.txt --json

or from the repository helper:

bashCopy code
python scripts/detect.py path/to/text.txt --json

5. Parse the JSON result and validate that it includes:

• score
• confidence
• verdict
• conclusion
• signals
• caveats

6. Respond in this order:

7. One-sentence conclusion with uncertainty.

8. Score and confidence.

9. Strongest evidence signals.

10. Caveats.

11. Next steps only when useful.

Output Guidance

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.

Repository Layout

• SKILL.md: skill contract and usage rules
• scripts/detect.py: repository-local wrapper for the detector
• scripts/setup.sh: local environment bootstrap
• references/api-reference.md: response contract and CLI reference
• assets/templates/report.md: reusable response template

Development Notes

• Keep the analyzer explainable and lightweight.
• Prefer local heuristics over hidden network calls.
• Update this file whenever behavior or output changes.