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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds value by noting cursor-based pagination and the sample tier rejection, which are beyond what annotations provide.

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 four sentences, front-loaded with the main action, and each sentence adds unique value (filters, pagination, tier limitation). No wasted words.

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?

Given the tool has an output schema and annotations, the description adequately covers all key aspects: what it returns, ordering, filters, pagination, and a notable limitation (sample tier). Nothing essential is missing.

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%, so the schema describes all parameters. The description adds context like case-insensitivity for ticker and details for status filter. It also explains cursor-based pagination, which enriches the parameter meaning.

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 clearly states it returns 'the caller's saved theses, newest-first' and lists specific filters (ticker, view, status). This distinguishes it from sibling tools like 'list_public_theses_by_user' (public vs own) and 'get_thesis' (single vs list).

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 implies it should be used to list the user's own saved theses, with filtering and pagination. It mentions 'Sample tier rejected (no per-user state)', which is a constraint but does not explicitly compare to alternatives like 'list_public_theses_by_user' or when not to use it.

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