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

readOnlyHint=true already establishes this is a safe read, and the description usefully adds the introspection-enabled prerequisite and explains the call's role as a discovery step. It does not, however, say what happens when introspection is disabled (error vs empty result) or anything about result size or pagination.

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?

Two sentences, zero filler: the first defines the resource and return content, the second states the recommended usage and the prerequisite. Front-loaded with the most decision-relevant information.

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?

With no parameters and no output schema, the description carries the return-value burden and does so by stating it returns flags with return types and descriptions. Minor gaps remain around failure behavior when introspection is off, but nothing needed to make the call correctly is missing.

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 tool takes zero parameters, so the schema imposes no semantics for the description to compensate for. The description correctly implies no arguments are needed, and the baseline of 4 for a no-parameter tool applies.

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?

States a specific verb (list) and resource (top-level feature flags / query root fields) and specifies what comes back: return types and descriptions, sourced from GraphQL introspection. The phrase 'before evaluating' implicitly differentiates it from hypertune_evaluate, so an agent can place it in the workflow without opening other schemas.

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 positions the call as 'a convenient first call to see what flags exist before evaluating,' which is clear when-to-use guidance, and adds a concrete prerequisite (introspection must be enabled on the edge endpoint). It stops short of naming the sibling tools (hypertune_introspect, hypertune_query) as alternatives or stating when not to use it.

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