tool_get_extensions

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

No annotations are provided, so the description carries the full burden. It discloses access requirements ('Requires instructor or TA access') and return format ('Returns a table of extensions with user ID, name, and modified dates'), which adds useful behavioral context. However, it lacks details on rate limits, error handling, or pagination, leaving gaps for a read operation with no annotation support.

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 appropriately sized and front-loaded: the first sentence states the purpose, followed by return details and access requirements, with parameter explanations in a clear 'Args' section. Every sentence adds value without redundancy, making it efficient and well-structured.

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's moderate complexity (2 parameters, no annotations, but with an output schema), the description is mostly complete. It covers purpose, access requirements, parameters, and return format. Since an output schema exists, it need not explain return values in detail, but it could benefit from mentioning sibling tool relationships or error cases for full completeness.

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 schema description coverage is 0%, but the description compensates by listing and briefly explaining both parameters ('course_id: The Gradescope course ID' and 'assignment_id: The assignment ID'). This adds meaning beyond the bare schema. However, it does not provide format examples, constraints, or links to other tools, so it meets the baseline for partial compensation.

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 the tool's purpose: 'Get all student extensions for a specific assignment.' It specifies the verb ('Get'), resource ('student extensions'), and scope ('for a specific assignment'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'tool_set_extension' or 'tool_modify_assignment_dates', which prevents a score of 5.

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 for usage: 'Requires instructor or TA access.' This indicates prerequisites and when the tool is applicable. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'tool_set_extension' for modifying extensions or 'tool_get_assignment_details' for general assignment info), 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.