Get how the learner did

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

Annotations already provide readOnlyHint=true and openWorldHint=true, so the description doesn't need to restate safety. It adds value by explaining what the read returns (weakCards, untouchedCards, review counts) and how to use it, which goes beyond the schema. No contradiction is present.

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 sentences, zero fluff. The purpose is front-loaded, and the usage guidance is packed into the second sentence. Every word 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?

Since an output schema exists, return values are covered. The description gives the loop context and the key fields, which is sufficient for an agent to select and call correctly. Minor gaps like pagination or error handling are not critical for a simple read 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 100%, so both setId and userId are already documented. The description adds no parameter-level detail beyond what the schema provides, so it doesn't compensate further, but it also doesn't detract. Baseline 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 uses a specific verb ('Read back') and identifies the resource ('real study results for a set') with concrete fields (weakCards, untouchedCards, per-card review counts). It clearly distinguishes itself from siblings like get_study_set by focusing on performance results, and explicitly frames this as the 'feedback half of the loop'.

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 gives explicit usage guidance: 'read it before writing the next set' and advises building follow-up from weakCards. This tells the agent exactly when to use this tool and how to act on its output, which is more explicit than most tool definitions.

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