qa_get_entitlement

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

There are no annotations, so the description carries the behavioral burden. 'Read' and 'server-authoritative' disclose that this is a read-only lookup from the server source of truth, but the description does not mention auth expectations, error behavior, or whether the data may be absent.

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?

A single front-loaded sentence states the verb and lists the exact data domains with no filler or repetition. Every word adds informational value.

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 parameterless read tool with no output schema, the description names all the data it returns, which is sufficient for an agent to invoke it. It does not describe return formatting or error cases, but the low complexity of the operation justifies this.

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?

The tool has zero parameters, and schema coverage is 100%, so the schema already fully documents the input. The description adds no parameter details, but none are needed; the 0-parameter baseline of 4 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 opens with 'Read' plus a specific resource (entitlement state) and enumerates its data fields: plan, status, billing product identity, and AI credits. Those fields distinguish it from sibling getters like qa_get_usage and qa_health even without naming them.

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 no explicit guidance on when to call this tool versus sibling tools, and no exclusions or alternative suggestions. The only usage signal is the verb 'Read', which is implicit rather than directive.

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