Five tools with clear naming (verb_noun pattern) and reasonable descriptions (100-200 chars). However, input schemas are not visible in the provided source code, only tool registration calls are shown. Parameter types, constraints, and output schemas cannot be verified. Descriptions are adequate but lack actionable detail (e.g., 'audit_site' does not explain what 'full compliance' means or what headers §4.5 requires). No evidence of error handling guidance or recovery paths. Tools are read-only and well-scoped, but schema documentation is a critical gap.

• Add explicit JSON Schema definitions for all tool inputs. Include type, description, enum constraints, and examples for each parameter. Reference the MCP SDK's tool registration API to ensure schemas are properly serialized.
• Document output schemas for each tool. Specify the structure of successful responses (e.g., 'parse_agents_txt returns {agents: Agent[], errors: ValidationError[]}') and error responses (e.g., 'validate_agents returns {valid: boolean, errors: {line: number, rule: string, message: string}[]}').
• Expand tool descriptions to 100 - 200 characters. Include WHEN to call the tool, WHAT it returns, and WHAT TO DO NEXT. Example: 'Parse a plain-text agents.txt file into structured JSON. Use this before validate_agents to check syntax. Returns {agents, errors}. If errors is non-empty, show the user the line numbers and rule violations.'
• Add parameter descriptions and constraints. For 'get_spec', clarify whether it accepts a section name (enum: 'overview', 'discovery', 'skills', etc.) or a full spec. For 'audit_site', specify whether it accepts a URL or domain and what headers it checks.
• Implement error recovery guidance. For 'validate_agents', return errors with line numbers and actionable messages (e.g., 'Line 42: missing required field "capabilities", see spec §3.2'). For 'parse_agents_txt', distinguish syntax errors from semantic issues.