list_peer_reviews

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description does not mention that this is a read-only operation, nor does it discuss pagination, output format, or any restrictions. It only states the literal action of listing assignments, adding no insight into side effects or edge cases. This is a significant gap for a tool with zero annotation coverage.

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 a single, front-loaded sentence that efficiently conveys the tool's purpose. It earns its place with the specific clarification of 'who's reviewing whom'. However, it is so terse that it lacks useful context like parameter hints, which other dimensions penalize; conciseness itself is good but not exceptional.

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 that an output schema exists, the description need not explain return values. However, it leaves out any mention of parameter requirements (though implied by the name) and provides no behavioral context beyond the basic action. For a simple list tool, this is minimally adequate but lacks details like whether it returns all peer reviews or only those for a specific assignment (though that is implied). It is sufficient for basic use but not comprehensive.

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 defines two parameters (course_identifier and assignment_id) with anyOf string/integer types, but the description provides no explanation of these parameters, what they mean, or how they relate to the tool's function. Schema description coverage is 0%, so the description must compensate, but it does not. An agent would have to rely solely on parameter names and the schema, with no contextual guidance.

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 uses the specific verb 'List' and resource 'peer review assignments', with the scope 'for an assignment' clearly stated. It distinguishes itself from siblings like assign_peer_review and delete_peer_review by focusing on listing existing assignments, and from list_assignments by specifying the peer-review subset. The parenthetical '(who's reviewing whom)' further clarifies the exact data returned.

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 provides clear context: this tool is used when you need to see peer review assignments for a particular assignment. It does not explicitly mention alternatives or when not to use it, but the context is sufficient for an agent to infer typical usage. No exclusions or alternative tools are named, so it falls short of a 5.

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