health_check

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare readOnlyHint=true and openWorldHint=false, indicating a safe, read-only operation with deterministic behavior. The description adds valuable context beyond this by specifying what gets checked (server configuration, AWS connectivity, service availability) and the tool's troubleshooting role. It doesn't contradict annotations, and while it doesn't detail rate limits or auth needs, the added context justifies a score above the baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, followed by specific use cases and return details. Each sentence adds distinct value without repetition or fluff, making it highly efficient and well-structured for quick comprehension by an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters), rich annotations (readOnlyHint, openWorldHint), and the presence of an output schema, the description is complete. It clearly explains the tool's purpose, usage guidelines, and what it returns, without needing to detail parameters or output structure, which are covered elsewhere.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose and output. A baseline of 4 is applied as per the rules for 0 parameters, as it efficiently avoids redundant information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('check', 'verifies') and resources ('AWS Security Posture Advisor MCP server', 'server configuration, AWS connectivity, and service availability'). It distinguishes from sibling tools like 'assess_security_posture' (which likely analyzes security) and 'get_server_info' (which likely provides general server information) by focusing specifically on health verification and troubleshooting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'Use this tool to troubleshoot connection issues or verify proper setup.' This provides clear context for usage and implicitly suggests alternatives (e.g., use other tools for non-troubleshooting purposes). It effectively guides the agent on appropriate scenarios for invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.