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Build a Structured Interview Kit

build_interview_kit
Read-onlyIdempotent

A lean structured interview loop for an engineering role: stages, owners, time budget, fixed questions, an anchored 1-4 rubric and a legal check of your questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleYesRole and level
detailsNoMust-haves (or a role scorecard), who can interview, any questions you already use

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered structurally. The description usefully signals the generated content (a legal check is run on the questions, the rubric is anchored 1-4), but it says nothing about whether the kit is persisted, its output shape, or whether it consumes any stored role data.

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?

A single front-loaded sentence with a colon-delimited list of deliverables; nothing is redundant. It is dense and slightly noun-phrase-heavy rather than imperative, but no sentence wastes space.

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?

With no output schema, the description carries the burden of describing return content and it does so by enumerating the kit's components, which is the most important thing an agent needs here. The remaining gap is routing guidance against the many interview-related siblings, which no other field supplies.

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% for both parameters, so the schema already explains 'role' and 'details'. The description adds no meaning beyond that — the enumerated kit components describe output, not inputs — so the baseline 3 applies.

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

Purpose4/5

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

The description names a concrete deliverable — a structured interview loop for an engineering role — and enumerates its parts (stages, owners, time budget, questions, 1-4 rubric, legal check), which is specific enough to distinguish it from question-only siblings like developer_interview_questions or design_coding_assessment. It does not, however, explicitly contrast itself with those siblings, and the verb is carried by the tool name rather than the text.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. With siblings such as design_coding_assessment, developer_interview_questions, build_role_scorecard and score_interview_notes, an agent must guess which one applies to a given request.

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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