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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower. The description still adds real value: the output includes 'what the interviewer is listening for, plus STAR answer tips', questions are derived from job-description skills/duties or the user's own roles, and it is 'Rule-based' (deterministic, not free-form generation).

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 trigger condition is front-loaded in the first clause, and the remaining sentences each add distinct information (output shape, input-dependent behavior, determinism). It is somewhat dense but every sentence 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?

With no output schema, the description carries the return-value burden and does so ('each with what the interviewer is listening for, plus STAR answer tips'). Trigger, both input modes, and output composition are all covered, leaving nothing an agent needs to call it correctly.

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 coverage is 100%, so baseline is 3, but the description goes beyond the schema by explaining the causal effect of the optional inputs: job_description drives questions from its skills and duties plus research pointers, and resume_text drives questions from the user's roles. The enum values and limit are left to the schema.

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+resource ('interview questions to practise') and its scope ('for a specific job or in general'). It implicitly distinguishes itself from the sibling review_interview_answer by generating questions rather than critiquing answers, but never names or contrasts a sibling explicitly.

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?

'Use this when the user is preparing for an interview and wants likely questions' gives a clear triggering context, and it explains the two operating modes (with job_description vs with resume_text). It stops short of stating when NOT to use it or naming an alternative tool for adjacent needs.

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