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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds value beyond them: it discloses that the response also carries the connected trainer_id and that it must be interpolated into paths like /v1/trainers/{trainerId}/students — a non-obvious behavioral detail. It does not mention pagination or result-size limits, keeping it just short of a 5.

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 purpose, filter mechanics and next-step routing are all front-loaded, and the domain list is compact prose rather than bullets. The long catalogue of domains (check-ins, chat, contracts, charges and payments, team, public page, AI generation and more) is somewhat sprawling, though it doubles as keyword hints. Appropriate overall length for a catalog/discovery tool.

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?

There is no output schema, so the description carries the return burden — and it does: it names the returned fields (method, path, summary) plus the trainer_id. Combined with the keyword semantics and the downstream tool routing, an agent has everything needed to call this correctly on the first try.

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 single keyword parameter is already documented, so the baseline is 3. The description goes further by stating the filter accepts values in Portuguese or English and listing concrete example keywords ("workout", "assessment", "diet", "appointment", "charge"), which is genuinely useful semantics the schema lacks.

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 (lists) and resource (Trainer Connect app operations this connection can run), and further specifies the returned shape (method, path, summary). The enumeration of covered domains and the explicit hand-off to describe_operation/api_read/api_write makes it immediately distinguishable from every sibling.

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?

Gives an explicit workflow: filter with a keyword, then call describe_operation for fields, then api_read or api_write to execute. It names the alternative tools and the condition that selects each, which is exactly the discovery-to-execution routing an agent needs.

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