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

Annotations already declare readOnlyHint=true and openWorldHint=false, covering safety. The description adds valuable behavioral context: it explains the output structure (domains with weakest first, comparison of misses), the 'traps' focus when misses follow common wrong answers, and the anonymous-caller behavior (told so rather than shown zeros). This goes beyond the annotations and helps the agent anticipate side effects and edge cases.

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 dense but efficient, with the core purpose front-loaded in the first sentence, followed by usage guidance, output details, and an important edge case. It avoids fluff and each sentence contributes to agent understanding. It is slightly long but warranted given the behavioral nuances.

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 tool with one parameter and no output schema, the description covers the essential aspects: what it does, when to use it, what output to expect (domain breakdown, comparison, 'traps'), and the anonymous-caller caveat. It does not specify the exact return format (e.g., JSON structure), but that may not be necessary for the agent to call it correctly. The description is sufficient for most use cases.

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?

The input schema covers the single parameter (exam) with a full enum and description ('Exam slug from list_exams'). The description adds minimal extra meaning about the parameter beyond what the schema provides; it only refers to 'one exam' in the opening sentence. Since schema coverage is 100%, the baseline of 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 what the tool does: it shows recorded history for an exam, broken down by blueprint domain with the weakest first, plus a comparison of misses against others on free-form questions. This is a specific verb+resource (shows history) and clearly distinguishes it from siblings like get_practice_question, which generates questions, or check_answer, which evaluates a single response.

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 explicitly tells the agent when to call this tool: at the start of a study session to decide what to drill, and after a run of questions to show what moved. It also mentions that it names the domain to pass to get_practice_question, effectively routing to a sibling. However, it does not state when not to use it (e.g., if no history exists) beyond the anonymous note, so it lacks explicit exclusions.

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