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

Annotations already declare a safe, read-only, closed-world operation, so the description's job is to add context beyond that. It does so by framing the call as a payment-verification step and enumerating the state it reflects, though it says nothing about latency, caching, or freshness of the payment status.

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, and it front-loads what the tool returns before the usage trigger. Every clause carries 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 output schema, the description must convey return values, and it enumerates them (stage, interview progress, payment status, next step). Combined with the strong trigger guidance and full schema coverage on the one parameter, an agent has everything needed 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?

There is a single parameter with 100% schema description coverage, and the schema already explains that studyId comes from create_study or list_studies. The description adds no format, sourcing, or validation detail, so the baseline of 3 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?

The description names the concrete returned artifacts (stage, interview progress, payment status, next step), so an agent knows exactly what a call yields, distinct from siblings like get_plan or get_findings. It never states an explicit verb for the tool itself, relying on the title, which keeps it just short of a top score.

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?

It gives a precise trigger condition ('when the user returns from the payment page') and asserts exclusivity ('the only way to know whether payment went through'), which tells the agent both when to call it and that no sibling covers this need.

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