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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the side effects (emails a one-time code), the expected follow-up (call verify_email), and the security implication (code is a Supabase Auth credential to treat as a secret). It also notes rate limits. It does not cover edge cases like invalid email or network failures, but the core behaviors are transparent. A score of 4 reflects strong disclosure that is not exhaustive.

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 well-structured with bold headers ('When to use', 'What happens', 'Limits') that front-load the critical purpose and usage, then provide sequential behavioral details. Each sentence serves a distinct purpose; there is no redundancy or filler. The length is justified by the tool's procedural complexity.

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 tool with a single parameter, no output schema, and no annotations, the description provides a thorough walkthrough of the expected flow, including how to obtain the code, the call to verify_email, and the handling of existing accounts. It also covers security and rate limits. It omits a few edge cases (e.g., invalid email format, network errors) but is sufficiently complete for an agent to use correctly. The missing edge cases are minor.

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 description coverage is 0%, meaning the description does not add any semantic detail about the 'email' parameter beyond the schema's format and pattern. The description mentions 'email address' generically but does not elaborate on constraints, validation, or usage nuances. Given the low coverage, the description was expected to compensate, but it does not, so the score is low.

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 precise statement of the tool's purpose: 'Create an Aient account from an email address, or get a sign-in code for an existing one, with no browser and no token.' This clearly identifies the verb, resource, and distinctive constraints, and implicitly distinguishes it from verify_email by describing the flow that uses that sibling. The purpose is unambiguous.

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 'When to use' section is explicit and actionable: it specifies the conditions (no token, workspace desired, or previous verify_email returned workspace_unavailable/expired token) and instructs to ask the user for the email. This gives clear guidance on when to invoke this tool versus alternatives, fulfilling the dimension's requirement.

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