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

With no annotations provided, the description carries the transparency burden. It discloses that results are grouped by curriculum source, that the return shape exactly matches GET /api/v1/public/courses, that no fields are added or removed, and that filters are applied to that endpoint's response rather than deriving a custom query. This gives meaningful insight into how the tool behaves, though it stops short of discussing pagination, sorting, or error behavior.

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 well organized: a one-line purpose, a concise Args list, and a short Returns paragraph. Every sentence adds information, and the most important purpose statement is front-loaded. Slightly verbose with the endpoint comparison, but the detail is relevant for understanding response behavior.

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 only two optional parameters, no annotations, and no output schema, the description covers the essential information: what the tool lists, how grouping works, what filters do, and the exact response contract via the referenced endpoint. The main gap is that it does not describe the actual fields returned by GET /api/v1/public/courses, so an agent may still need to discover the shape elsewhere. Otherwise it is largely complete for a simple public list tool.

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 0%, so the description must compensate. It does so by explaining audience as an optional filter with values 'k12' or 'adult' and language as an optional filter matching the display name of the 'language' field, with examples. This adds real meaning beyond the bare schema (string/null + name). It could be even stronger by indicating case sensitivity or exact-match behavior, but it is already quite helpful.

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 opens with a specific verb and resource: 'List Epivo's public course catalogue, grouped by curriculum source.' This clearly states the operation and is distinct from the sibling tools get_catalog_stats and get_course_detail, which focus on statistics and individual course details rather than the full catalogue listing.

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 when to use the tool—whenever the full public course catalogue is needed—and provides filter parameters for narrowing results. However, it never explicitly contrasts itself with get_catalog_stats or get_course_detail, nor does it state conditions such as 'use this for browsing, use get_course_detail for a single course.' Usage guidance is present but only implicit.

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