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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds further behavioral clarity: 'Deterministic and stateless — nothing is stored server-side.' It also explains the two-phase interaction pattern and the precise output semantics (continuous 0-100 values, never categorical labels). This is valuable context beyond the structured annotations and no output schema is present, so the description carries the burden well.

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 compact yet information-dense, using four sentences to cover purpose, usage, integration, and behavior. It is front-loaded with the most important action and output constraints, then flows logically into invocation, storage, and determinism. No redundant filler or repetition of schema details.

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 tool's moderate complexity, one optional parameter, and no output schema, the description adequately covers the full interaction contract: how to request questions, how to submit answers, what the output profile is, what to do with it, and backend behavior. It also includes a schema URL for further reference. The context is complete for an agent to select and invoke the tool 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?

Schema description coverage is 100%: the answers object documents each primitive and its a/b/c enum, and the schema description says 'Omit entirely to receive the questions.' The tool description adds meaning by explaining what the answers represent behaviorally and how they map to a continuous profile. It doesn't need to repeat schema details, and it supplements with the two-mode semantic difference, so a strong score is warranted.

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 opens with a specific verb and resource: 'Build a ReceiverProfile (TI, SG, FT, UE, AR — continuous 0-100, never a category label) from five behavioral forced-choice answers.' This clearly distinguishes calibrate_profile from siblings like interpret or normalize by describing its unique role in constructing a receiver profile. It also explains the two invocation modes (no answers vs. with answers), further clarifying purpose.

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?

Explicit usage instructions are provided: 'Call with NO answers to get the five questions to ask the user; call again with their answers (a/b/c per primitive) to get the profile.' It also states when the output should be used: 'Store the returned profile JSON in the user’s notes or memory and pass it to render_reply / prepare_prompt on every turn.' This gives clear when-to-use and integration guidance beyond what schema or sibling names imply.

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