edubase_post_exam_users_generate

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

Annotations already declare non-readonly, non-destructive behavior, but the description adds valuable context by explaining that patterns are stored with the exam and reused as defaults for future calls. It also discloses the interaction between count and names (count ignored when names is provided). However, it does not detail side effects like whether existing accounts are overwritten or what happens on partial success.

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 well-organized: it leads with the core purpose, then explains placeholders, and ends with persistence semantics. Sentences are information-rich with no filler, though it could be slightly trimmed. The structure is logical and front-loaded.

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 eight parameters and complex rules, the description covers pattern syntax, parameter precedence, and defaults. Given that an output schema exists (though not shown), the lack of return-value details is acceptable. What is missing is explicit guidance on required permissions or error handling, but overall it is comprehensive enough for correct invocation.

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 descriptions cover 100% of parameters, but the description adds critical semantic relationships: placeholders usable in patterns, the defaulting behavior for name/password/username, and the constraint that emails must match names in count. These details are not fully captured in the schema and materially improve correct usage.

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 specific verb ('Generate') with a clear resource ('exam accounts') and the assignment target ('assign them to an exam'). It distinguishes the tool's batch-generation intent from simpler account creation tools by detailing placeholder-based pattern generation, leaving no ambiguity about what the tool does.

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 when to use this tool (bulk account generation for an exam) but does not explicitly mention alternatives or when NOT to use it. It provides clear functional context, yet lacks direct exclusionary guidance. The behavior of pattern defaults and ignored parameters helps infer usage, but it is not as explicit as it could be.

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