The server exposes a single tool 'scan_url' with a well-defined purpose: fetch and scan URLs for prompt injection attacks. The tool has a clear, actionable description (113 chars), proper naming following verb_noun convention (scan_url), and a complete input schema with type and description. However, there are notable gaps: the output schema is not documented in the code, error handling returns raw JSON without actionable recovery guidance, and the tool lacks annotations (readOnlyHint, idempotentHint) that would help agents reason about safety. The implementation is functionally solid but missing patterns expected in production-grade tools.

• Document the output schema explicitly: specify that scan_url returns an object with 'status' field (enum: 'clean'|'injection_detected'|'error'), and the structure of each response variant. E.g., clean response includes 'content' (string), injection response includes 'threats' (array of threat objects with type and description), error response includes 'message' (string) and 'url' (string).
• Add tool annotations when registering the tool. Mark it with readOnlyHint: true (it only reads web content, no side effects) and idempotentHint: true (same URL produces same result on repeated calls). This signals to agents that the tool is safe for retry and exploration.
• Enhance error messages with recovery guidance. Instead of 'URL rejected by SSRF guard: <url>', return structured error like '{status: "error", code: "ssrf_blocked", message: "URL points to a private/internal IP and was blocked for security. Try a public URL instead, or contact the admin if this is a corporate resource."}' This guides the agent's next step.
• Add parameter validation examples to the description. The url parameter accepts valid HTTP(S) URLs up to 2048 chars, but consider adding: 'URLs must be publicly accessible (no private/internal IPs). Public URLs like https://example.com/page are supported; localhost, 127.0.0.1, 10.*.*.*, 192.168.*.*, and IPv6 private ranges are rejected.'
• Consider adding a max_response_size_kb parameter (optional, default 1024) so agents can control memory usage for very large pages, or document the implicit limit in the description.