Security audit
Security checks for vulnerabilities and agentic risk
This skill is locally implemented and disclosed, but it is designed to help users reduce platform AI-detection signals before publishing social posts.
Review before installing if you publish on platforms with AI-content or authenticity policies. The code appears local and limited to text analysis, but its main value is helping content look less AI-detectable, so avoid using it to mislead audiences or bypass platform rules.
The file header explicitly frames the tool as measuring signals platforms use to detect AI-generated content and helping users identify which signals to change. That makes the skill an optimization aid for evading platform integrity and moderation systems, even if it does not directly rewrite text itself.
The recommendations give concrete, actionable steps for making text appear more human and lowering an 'AI signature,' such as adding contractions, pronouns, questions, and removing flagged words. This is effectively coaching for stealth/evasion against social-platform AI-content detection systems.
The skill advertises command examples that read local files (--file draft.txt) and piped stdin, but it does not declare any tool scope or permissions boundary. In an agent ecosystem, undeclared file-read capability weakens reviewability and can lead to broader-than-expected access to local content when the skill is invoked.
Although framed as an 'auditor,' the skill explicitly tells users which platform-detection signals to change so content is less likely to be flagged as AI-generated. That is effectively evasion guidance for trust-and-safety or ranking systems, enabling users to disguise synthetic content rather than merely assess it.
This section provides step-by-step remediation actions—add contractions, add specific data, remove flagged words—and explicitly states these changes lower the 'AI signature' by 20-30%. That is concrete, actionable bypass guidance for stylometric AI-detection systems, which increases the likelihood of deceptive or policy-evading use.
The introductory text presents the tool as an auditor for the exact signals used by platforms to detect AI-generated content. In context, that framing supports iterative testing and refinement of content until it passes, which lowers the effectiveness of authenticity controls.
The top-fix recommendations are explicit coaching instructions for reducing detection risk by altering linguistic markers associated with AI text. That materially increases the usefulness of the tool for incremental evasion, especially when combined with per-platform verdicts and thresholds.
No suspicious patterns detected.
