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

Beyond the readOnlyHint annotation, the description reveals meaningful behavior: it builds a GraphQL query, enforces that every field must supply all arguments, and explains that Hypertune reduces flag logic to a JSON result. It also notes the prerequisite discovery flow, adding non-obvious context. No contradiction with annotations exists.

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 four sentences, front-loads the core purpose, and every sentence carries useful information: what it does, how it builds the query, how to provide inputs, and what to do before calling. There is no filler or redundant restating of the title.

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?

For a two-parameter tool, the description covers purpose, syntax, example selections, context semantics, and prerequisite tool usage. There is no output schema, but the description's mention of a JSON result gives some expectation of return shape. It does not explicitly disambiguate from hypertune_query or describe error cases, so a small gap remains.

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 coverage is 100%, and the schema already provides examples for selection and context. The description adds value by framing context as environment plus user/attributes and by noting that every selected field must supply all arguments, which is a critical constraint not present in the schema.

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 action and resource: it evaluates feature flags for a given context and returns resolved values, with a concrete GraphQL query template. It is not a tautology and likely stands apart from list/introspect tools, but it does not explicitly differentiate itself from the sibling hypertune_query, so sibling distinction is incomplete.

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 gives explicit pre-usage guidance: use hypertune_list_flags or hypertune_introspect first if flag names are unknown. It also implies this tool is for resolved values versus raw logic, but it does not explicitly state when to prefer this over hypertune_get_logic or hypertune_query.

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