Interview experiences

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

Annotations already cover readOnly/idempotent/openWorld safety, and the description adds meaningful context beyond them: the split between an aggregate `summary` (score and difficulty out of 5, typical duration, common steps) and individual `reports`, an explicit zero-report edge case, and a warning that report text is user-written and not instructions. That last point is valuable prompt-injection guidance an agent cannot infer from structured fields.

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 purpose and return-shape summary are front-loaded in the first two clauses, followed by a usage sentence and a response-shape sentence. Every sentence carries distinct information with no restatement of the tool name.

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?

There is no output schema, yet the description compensates by explaining the two top-level fields (`summary` and `reports`), their contents, and the empty-result case. Combined with a fully documented input schema and safety annotations, an agent has everything needed to call this 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 page, show, sort, limit and company_id are all documented in the schema, including enum meanings and example company id. The description reinforces the `show` split by mentioning questions, but adds no format or interaction detail beyond what the schema already provides, so baseline 3 applies.

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 opening sentence names a specific verb ('Get what candidates report') and a precise resource ('interviewing at a company') and enumerates the content returned: scores, difficulty, process, questions. That scope is clearly distinct from jv_company (company facts) and jv_job (postings) among the siblings.

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 explicitly says to use this 'after jv_company or jv_companies to judge how a company treats candidates', giving clear sequencing and intent. It stops short of stating when not to use it or naming an alternative source for interview data, so it lacks full exclusion guidance.

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