Update a study set

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

Annotations already signal mutability (readOnlyHint=false) and non-destructiveness (destructiveHint=false). The description adds a valuable side effect beyond annotations: 'Replacing the cards resets what the learner has already studied,' which is a behavioral consequence not captured in structured fields. It also warns against combining addCards and cards, adding safety context.

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?

Two tight sentences carry all essential information: the action, the two operational modes, the constraint, and a key side effect. No filler, front-loaded with purpose, and every phrase earns its place.

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?

For a mutation tool with 8 parameters, the description provides enough to call it correctly: it explains the main operational choices, the safety constraint, and the meaningful side effect. The output schema covers return details, and remaining parameters are straightforward. Nothing an agent needs is missing.

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 only 38%, so the description must compensate. It does so by explaining the two most ambiguous parameters—addCards (append) and cards (replace)—and their mutual exclusivity, plus the learning-reset consequence. Other parameters (title, topic, visibility) are self-explanatory, and the critical ones are well addressed, bridging the coverage gap.

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 names a specific action ('Change a set in place') and lists concrete operations (retitle, retag, add cards), clearly distinguishing it from create/delete/list siblings. The verb 'change' and resource 'study set' are explicit, and the added detail on cards vs. addCards further sharpens the purpose.

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?

Provides explicit guidance on choosing between addCards (append, 'the usual case after reviewing results') and cards (replace wholesale), including the 'never both' constraint. It implies when to use the tool (modifying an existing set) but does not directly contrast with create_study_set for new sets; however, the parameter-level usage is well covered.

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