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

The readOnlyHint annotation already covers safety, and the description adds useful behavioral context by explaining that results come from GraphQL introspection and that introspection must be enabled on the edge endpoint. This is meaningful operational information beyond the annotation. No contradiction 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 three concise sentences with no filler. The main action and result are front-loaded, followed by workflow context and a prerequisite. Every sentence earns its place, and the overall structure is easy to scan.

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 simplicity of the tool and the absence of parameters, the description covers the essential points: what is listed, how it is derived, when to use it, and what must be enabled. It does not explicitly contrast the tool with the sibling 'hypertune_introspect', but the 'top-level flags' scope and 'before evaluating' framing provide enough context for an agent to call it correctly.

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?

With zero parameters, the parameter-semantics burden is minimal, and the baseline is 4. The description effectively explains what the tool returns, which is sufficient for a parameterless call. There are no parameter semantics to clarify beyond that.

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 that the tool lists the project's top-level feature flags, specifically the fields of the query root type, along with their return types and descriptions. It also identifies the data source as GraphQL introspection, which gives a precise scope and distinguishes the tool from evaluation-focused siblings.

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 phrase 'A convenient first call to see what flags exist before evaluating' gives explicit guidance on when to use the tool in a workflow. It also mentions the introspection prerequisite. It does not name alternative tools or conditions when not to use it, so it is strong but not fully explicit about exclusions.

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