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

Annotations already cover readOnly/idempotent/non-destructive/non-openWorld, so the bar is lower, and the description still adds that the tool is 'rule-based' (deterministic, no external lookup) and that output varies by supplied inputs. It does not describe limits, defaults, or output shape beyond the content itself.

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 tightly written sentences with the core deliverable front-loaded and the conditional input semantics following immediately; 'Rule-based.' earns its place as a one-word behavioral signal.

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?

No output schema exists, so the description carries the return-value burden and does so by enumerating what each question includes (listening cues, STAR tips, research points, questions to ask). Nothing essential for correct invocation is missing.

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 the baseline is 3, but the description adds real meaning by explaining how job_description and resume_text change what is returned. The kind enum and limit are left entirely to the schema, which is acceptable.

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?

States a concrete verb+resource: it produces interview practice questions with listening cues and STAR tips. The content is specific enough that an agent can tell it apart from review_interview_answer (which evaluates an answer), though it 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?

Gives clear conditional usage: with a job_description the questions derive from its skills and duties; with resume_text they come from the user's own roles. It omits any when-not guidance or explicit routing to alternatives such as review_interview_answer.

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