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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the agent knows this is a safe, closed-domain read. The description adds meaningful context beyond that: it clarifies the tool does not itself perform signup, and that the follow-up sequence is my_shearquery_account then set_my_account_type. It does not describe how the clarifying questions are surfaced, but with annotations carrying the safety profile, this is strong.

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?

Front-loaded with the purpose, followed by the account types, then the signup routing. Every sentence carries useful information, though the parenthetical type list and the flow instruction pack a lot into a few clauses and could be marginally tightened.

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-required-parameter decision helper with no output schema, the description covers what the tool does, the types available, the signup routing, and the anti-guessing rule. The only minor gap is an explicit statement of what the tool itself returns before a type is chosen, though the schema description covers the post-decision return.

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 coverage is 100% with a single optional enum parameter, and the schema description already states 'Once decided, returns that type's details and signup link.' The description adds only the behavioral rule 'do not guess the type from one word,' which does not extend the enumeration or value semantics. Baseline 3 is appropriate.

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?

States a specific function: helping someone choose and create the right ShearQuery account, listing the nine account types and what each gets. It explicitly distinguishes itself from the actual signup flow by naming the sibling tools my_shearquery_account and set_my_account_type, so an agent can tell this decision-helper apart from the tools that perform the mutation.

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 describes routing: use my_shearquery_account then set_my_account_type to sign up (not a website link), and instructs 'Ask the questions in conversation; do not guess the type from one word.' This gives both the when-to-use condition and the correct alternative flow.

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