ai-text-detector: A cautious, explainable AI text detector for local workflows and coding agents

by lynote-ai · Codex Skill · ★ 452

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 76/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-toolsai-content-detectionai-content-detectorai-detectorai-generated-text-detectionai-text-detectorai-writing-detectorchatgpt-detectorclaude-codecodex-skill

Quick Facts

Stars452
Forks20
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score76/100
Open Issues3
Last Updated2026-10-13
Created2026-05-25
Platformsclaude-code, codex, python
Est. Tokens~15k

About ai-text-detector

Best AI Text Detector An explainable, cautious AI-generated text risk analyzer for coding agents and local workflows. 简体中文 · Install · Evaluation · Use Cases Other Quality Projects AI Humanize Text:https://github.com/lynote-ai/humanize-text AI Image Detector:https://github.com/lynote-ai/ai-image-detector Why This Exists Most AI text detectors are either overconfident, opaque, or awkward to embed...

Compatible Skills

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  • humanize — semantic(0.52)+complementary+rare_topics+similar_pop (62%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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