get_latency_analytics

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds critical behavioral context: Enterprise-gated and returns 403 on non-Enterprise plans, which annotations do not cover.

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 very concise: three sentences, front-loaded with what the tool does, then usage guidance, then behavioral note. Every sentence adds value, no redundancy.

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 complexity (29 parameters, legacy/structured aliases, output schema exists), the description covers output details, usage context, and access restrictions. Missing explicit mention that output is time-series, but implied. Slightly short of 5 due to lack of more detail on time-series structure.

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 description coverage is 100%, so baseline is 3. The description does not add any parameter-level information beyond the schema; it only mentions output fields. Thus, no additional value for parameter semantics.

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 uses a specific verb 'get' and resource 'latency time-series data', lists output fields (summary.avg_latency_ms, etc.), and distinguishes from sibling 'get_cache_hit_latency' by stating when to use each.

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?

Explicitly states when to use: 'to spot slowdowns and regressions'; provides alternative: 'use get_cache_hit_latency when you only want cache-hit latency'; also notes Enterprise-gating, guiding non-Enterprise users away.

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