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Practise an interview, one question at a time

interview_practice
Read-onlyIdempotent

Practise an interview, one question at a time. For "practise an interview with me" or "how was that answer?". Send the role to get the first question; send the question and the person's answer to get a score out of 10 with what went well, one thing to fix and the next question. Scored by fixed rules, the same for everyone: structure (situation, task, action, result), what the person did themselves, a concrete result, length and the question's own words. It scores the answer, never the person, and nothing is stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoWhich practice question to ask, from 0. The reply gives next_n.
roleNoThe job being interviewed for, for example "staff nurse".
answerNoThe person's answer, as they would say it. Leave out to get the next question.
questionNoThe question that was answered, copied from the last reply. Leave out to get a question.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and idempotentHint=true, so the safety profile is covered. The description adds substantive behavioural context beyond the annotations: fixed scoring rules, what each score covers, that it never scores the person, and that nothing is stored. It does not explain the idempotency semantics or reply format boundaries, which keeps it short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well front-loaded: purpose sentence, then usage, then scoring criteria. The middle list of scoring criteria is dense but useful. Slightly long, though every sentence carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-required-param read-only tool with full schema coverage, the description covers intent, flow, scoring behaviour and privacy. It omits what the 'n' / next_n handoff looks like in practice, which is a minor gap given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds conversational framing for role/answer/question and mentions max 6 via context, but does not extend the parameter documentation beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource (practice an interview, one question at a time) and names trigger phrasings ("practise an interview with me", "how was that answer?"). It is clearly distinguishable from siblings like interview_prep, which presumably prepares rather than interactively drills.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use triggers and layering instructions: send role for first question, send question+answer for a score and next question. The alternative path (interview_prep) is inferable from the sibling name though not named, but the usage flow is fully spelled out.

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

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