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

Beyond the readOnlyHint annotation, the description discloses a meaningful data-integrity behavior: unresolved requirement items are 'never guessed into this list,' which tells the agent results are conservatively filtered rather than exhaustive. It also outlines the item shape returned, adding value the annotation does not cover.

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?

Three short sentences, front-loaded with the core question, then the returned fields, then the accuracy caveat. No filler or repetition — every sentence carries information.

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?

With no output schema, the description usefully characterizes the return payload (checklist id, award, group heading) and the resolution semantics, which is what an agent needs to interpret the answer. It stops short of describing pagination behavior, though limit/offset are self-documented in the schema.

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 the schema already documents limit, offset, and learning_unit_id, including the example id and where to obtain it. The description adds no syntax, format, or defaulting detail for the parameters, so the baseline of 3 applies.

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 states a precise reverse-lookup purpose ('Which checklists require this course?') and enumerates what each returned item contains (checklist id, award, group heading). It is clearly distinguishable in direction from siblings like find_checklists and get_checklist, though it never names them explicitly.

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?

Usage is implied by the natural-language framing of the question, and the parameter description points the agent at learning_units/get_learning_unit as the source of the id. However there is no explicit when-to-use/when-not statement and no named alternative for adjacent needs such as browsing checklists.

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