get_service_health

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds that it's read-only with no side effects, details return fields (score, status, contributing metrics, error summary, anomalies, correlations), and clarifies behavior for services with no data (explanatory result not exception).

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?

Description is concise with no filler. Front-loaded purpose and usage, structured logically. Every sentence adds value.

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?

Tool has 1 parameter, no output schema, but description fully covers purpose, usage, behavior, and return fields. No gaps given the complexity.

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?

Schema covers the 'service' parameter with clear description and example. Description reinforces the need for exact case-sensitive name from list_services. Adds useful context beyond schema for one parameter.

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?

Description explicitly states it produces a single aggregated health verdict for one service using metrics and logs. It distinguishes from sibling tools like query_metrics/query_logs and detect_anomalies, making the purpose clear.

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?

Provides explicit when to use ('fastest way to answer is this service healthy'), when not (alternatives named), and prerequisites (get service name from list_services). Comprehensive guidance.

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