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

With no annotations, the description carries the full burden, and it discloses the OAuth requirement up front, the data returned, and the authorization_required response with connect URL when the token is missing. This covers the key behavioral edge case an agent would need to handle, though it does not discuss pagination or data freshness.

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?

Two sentences, front-loaded with the OAuth prerequisite, then the purpose and returned fields. Every sentence earns its place and there is no filler or repetition.

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 no-parameter read tool with no output schema, the description names the return fields and the auth error case, which is sufficient for an agent to call and interpret the result. It does not explicitly say whether multiple subjects can be returned, but the plural tool name and field list make that a minor gap.

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 input schema has zero parameters, so there is nothing for the description to add beyond the baseline. The 0-parameter baseline applies, and the description appropriately avoids inventing parameter details.

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 verb ('Lists') and the exact resource: the person whose exposure the account has checked, plus the returned fields. The mention of subject_id differentiates it from sibling tools like list_my_cases by clarifying it provides the identifier other personal tools need.

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 phrase 'subject_id other personal tools need' gives a clear use case for calling this tool. However, it does not explicitly name alternatives or state when not to use it, so the usage guidance is implied rather than explicit.

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