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

Annotations already mark the tool read-only, idempotent, and non-destructive, so the description builds on that by revealing return details: onboarding.completed and onboarding.missing_steps types, the optional frequency-capped nudge, and the explicit statement that billing/token metadata is not exposed. This is meaningful behavioral context beyond the annotations.

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 long but every sentence adds value: purpose, when to call, return values, nudge behavior, and data-scope caveats. It is front-loaded with the core purpose buck. It could be slightly tightened, but no filler is present.

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 carries the burden of explaining return semantics and does so well: onboarding.completed, onboarding.missing_steps with allowed values, the optional nudge and how to handle it, and the privacy boundary of not exposing billing/token metadata. It also gives the exact call timing ('once at the start of a conversation'). This fully equips an agent to invoke and interpret the tool.

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 and the schema description confirms 'No parameters required.' Per the rubric, 0 params is a baseline 4; the description also restates this clearly, so no additional parameter meaning is needed.

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: 'Get the connected user's profile, plan, onboarding state, team memberships, and note quota in a single call.' This precisely defines what the tool does and enumerates the data it returns, leaving no ambiguity about its purpose. The reference to 'connected user' clearly identifies the resource scope.

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?

Explicitly instructs when to call: 'Call this once at the start of a conversation' and explains why—greeting by first name, running onboarding, routing notes, and avoiding Pro upsells to free users. This is concrete usage guidance that an agent can act on immediately, even without a sibling comparison.

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