Three well-named, verb-first tools with solid descriptions (100-150 chars each). All tools have input schemas with typed properties and descriptions. Audit logic is sophisticated and demonstrates deep knowledge of LLM-usability patterns. However, output schemas are not explicitly documented in the source, parameter descriptions could be more detailed (e.g., 'tool' param in audit_tool_definition lacks format guidance), and error handling is not visible in the provided code. The server itself is a meta-auditing tool, so it does not expose destructive operations, security and composition concerns are lower priority.

• Document the output schema for each tool. Specify the structure of audit reports (e.g., { score: number, issues: array, fixes: array }) so callers know what fields to expect.
• Enhance the 'tool' parameter description in audit_tool_definition: 'A tool definition object with required fields: name (string, snake_case), description (string, 10-1024 chars), and optional inputSchema (JSON Schema object).'
• Add size/limit guidance to audit_tool_batch: 'Array of up to 100 tool definitions. Each tool must have a name and description.'
• Document the MCPIZE_SHORT_DESC_LIMIT (500 chars) in check_marketplace_description description and explain what happens if exceeded.
• Add explicit error handling examples: 'If a tool has no name, returns { score: 0, issues: [{ severity: "error", issue: "Tool has no name" }] }' to guide LLM interpretation of failures.