All 5 tools have identical, severely deficient schemas: empty properties objects with additionalProperties: true, providing zero type information or constraints. Descriptions are present (50-100 chars) but generic and marketing-focused rather than operationally useful. No parameter documentation exists. Tools appear to be payment/metadata bridges rather than functional MCP tools, they return hardcoded URLs and notes rather than actionable data. The server is a 'no-secret stdio MCP metadata bridge' that does not implement real tool functionality.

• Replace empty input schemas with explicit parameter definitions. Example: agent_security_policy_pack should define required params like 'policy_type' (enum: 'default-deny'|'allowlist'|'audit'), 'caps' (object with numeric limits), 'scope' (string describing permissions). Add descriptions for each param.
• Rename tools to start with action verbs: 'get_security_policy_pack' or 'fetch_payment_policy_compiler' instead of 'agent_security_policy_pack'. This lets LLMs infer intent from the name alone.
• Expand descriptions to 150-250 chars explaining: (1) What the tool does, (2) When to call it, (3) What it returns. Example: 'Retrieves a pre-configured security policy pack for AI agents. Call this before deploying an agent to set default-deny rules, caps, and audit schemas. Returns policy JSON and enforcement endpoints.'
• Document the output schema explicitly. Define fields like {tool: string, protocol: string, network: string, payTo: string, paidUrl: string, paymentQuote: string, checkout: string, revenueSummary: string}. Add descriptions for each field so LLMs know what to extract.
• Implement actual tool functionality or split into discovery tools. If this is a metadata bridge, rename to 'list_x402_payment_products' or 'get_x402_checkout_metadata' and document that it returns payment URLs, not operational data. If tools should perform real actions (compile policies, reconcile payments), implement those operations and return structured results.