Single tool 'secure_audit' has a clear, well-written description (127 chars, within 10-1024 range) and explicit input schema with type and description. However, the tool lacks output schema documentation, the AuditResult record is defined in code but not exposed in the tool definition. No error handling guidance, no parameter constraints (snippet length unbounded), and no recovery hints. The tool name 'secure_audit' is acceptable but generic; 'audit_compliance' or 'check_ai_compliance' would be more action-oriented. Overall definition quality is fair but incomplete for production use.

• Document the output schema in tool metadata: { riskScore: number (0-100), classification: string (LOW|MEDIUM|HIGH|CRITICAL), violations: array of strings }. This enables LLMs to extract and reason about results.
• Add input constraints: 'snippet' parameter should specify max length (e.g., 10000 chars) and acceptable formats (code, text, config). Include error guidance: 'If snippet exceeds 10000 chars, split into multiple audits.'
• Rename tool to 'audit_compliance' or 'check_ai_compliance' to lead with the action verb. This improves LLM tool selection and makes intent clearer in multi-tool scenarios.
• Expand parameter description to include examples: 'The code snippet or text to audit (max 10000 chars). Examples: Python code, SQL queries, API keys, email addresses. Detects EU AI Act violations (social scoring, biometric surveillance) and PII (SSN, credit cards, API keys).'
• Add error handling: catch regex timeout exceptions and return a structured error with retry guidance: { error: 'Snippet too complex for analysis', suggestion: 'Try splitting into smaller chunks or removing comments.' }