list_categories

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 that the tool returns a specific set of fields and supports filtering and pagination, which is adequate for a list operation. However, it does not reveal any behavioral traits such as rate limits, permission requirements, or whether results include only active categories by default—leaving some gaps.

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 concise—four short, front-loaded sentences—with no unnecessary words. Every sentence adds value: listing return fields, filtering options, use cases, and a cross-tool tip. It is appropriately sized for the tool's complexity.

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 5 parameters with 100% schema coverage, no output schema, and is a straightforward list operation, the description covers the key information: what data is returned, filtering, pagination, and how to leverage the data with other tools. It is comprehensive enough, though it could mention default limit/offset behavior for total 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?

Schema description coverage is 100%, so each parameter already has a clear description in the schema. The tool description adds minimal extra meaning beyond what the schema provides, but it does contextualize filtering by mentioning 'parent ID, exact parent name, and pagination' in a usage-oriented way. This justifies the baseline score of 3.

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 a specific verb ('list') and resource ('LMS categories'), and it clearly distinguishes the tool from siblings by detailing what it returns (e.g., path, depth, course count) and how it can be used for filtering. This differentiates it from tools like 'list_courses' or 'search_courses_by_name'.

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 explicitly states when to use the tool ('discover available categories, identify active vs inactive categories, and filter courses by category') and provides a practical pointer to use the exact category ID with other tools. However, it does not mention when not to use it or name specific alternatives among the many siblings, so it lacks explicit exclusions.

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