Get study set contents

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

Annotations already declare readOnlyHint=true, so the description doesn't need to repeat that it's a read operation. The description adds valuable context beyond the annotation by specifying the exact content returned: 'every card, plus the topic and notes you attached when you created it.' This enriches the agent's understanding of what the tool provides without contradicting any annotation.

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 a single, front-loaded sentence that starts with the verb 'Read,' immediately conveying the action. There is no fluff or redundancy. It efficiently conveys the scope of the tool in a way that is easy to scan, earning a full score for conciseness and structure.

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 that an output schema exists (has_output_schema=true) and the single parameter is documented in the schema, the description need not explain return formats or parameter formats. The description covers the necessary contextual information—what data is returned (all cards, topic, notes)—which is sufficient for an agent to call the tool correctly. There is no missing information that would impede correct usage.

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%; the parameter setId has a clear description ('Set id returned by create_study_set or list_study_sets'). The tool description adds no additional information about the parameter—it doesn't mention setId at all. Since the schema fully documents the parameter, the description does not need to compensate, so baseline 3 is appropriate.

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 a specific verb ('Read') and resource ('full contents of a set'), and specifies exactly what is included (every card, topic, notes). This distinguishes it from sibling tools like list_study_sets (which likely provides summary metadata) and get_set_results (which likely returns performance data). The agent can immediately understand what the tool does without opening the schema.

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 this is the tool to use when you need the full contents of a study set, but it does not explicitly mention when not to use it or name alternatives. For example, it doesn't say 'use list_study_sets for a summary' or 'use get_set_results for results.' There is no explicit guidance on choosing among the related collection/read tools, leaving the agent to infer when this one is appropriate.

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