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

Beyond the sparse annotations (only destructiveHint: false), the description thoroughly discloses behavior: returns needs_login if not authenticated, returns a question bank plus an adaptive protocol with specific patterns (one question at a time, concept then scenario, hint when stuck, scorecard). This adds significant context about expected behavior and safety.

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 efficient, with each sentence contributing purpose, parameter clarification, behavioral notes, or next steps. It is not as minimal as the two-sentence ideal, but the extra context about login and the adaptive protocol is valuable and not redundant.

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 the sparse annotations and 0% schema coverage, the description carries the full burden and covers all critical aspects: input source, authentication requirements, return value, and follow-up action. The output schema handles return structure, so no additional return-value detail is needed.

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?

With 0% schema description coverage, the description compensates by explaining that `interview` is a topic id from list_interviews and that `role`/`experience` calibrate difficulty. It does not explicitly describe auth_token, but the login requirement implies its purpose, giving meaningful semantic coverage beyond the raw 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 opens with 'Begin a curated Interview-Prep session on a fixed topic', which is a specific verb+resource construction that clearly states the tool's function. It distinguishes itself from sibling tools like list_interviews (listing topics) and start_exam (exams) by focusing on starting a prep session.

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?

It provides clear context for when to use the tool, including that `interview` comes from list_interviews and that a login is required (with instructions not to run questions if not logged in). It also mentions saving with save_interview, but does not explicitly contrast with alternatives like interview_prep, leaving a small gap.

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