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

No annotations are provided, so the description carries the full behavioral burden. 'Return' implies a read-only retrieval, but the description does not disclose authentication requirements, rate limits, side effects, or response format, leaving most behavioral traits unspecified.

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 a single front-loaded sentence with no filler. The list format is dense but appropriate for enumerating the endpoint categories returned.

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 zero-parameter read tool, the description is adequate enough to invoke correctly, but with no output schema it does not explain the returned data structure, and it leaves usage context thin. It covers the purpose but not the full context an agent might need.

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 takes zero parameters, so there are no parameter semantics for the description to clarify. Per the rubric, a zero-parameter tool receives a baseline of 4.

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 a specific verb ('Return') and resource ('self-service REST enrollment, Stripe wallet funding, paid-job and polling endpoints'), making the tool's purpose clear. It does not explicitly differentiate itself from siblings like get_machine_wallet or get_paidhandshake_capabilities, but the onboarding focus is distinct enough to be actionable.

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 identifies the target audience ('autonomous agent buyers') but gives no when-to-use guidance, prerequisites, or comparisons to sibling tools. An agent must infer that this is the entry point for machine onboarding rather than being told directly.

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