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Wizeb AI-Native Index

Get the 30 AI-Native Index questions

get_index_questions
Read-onlyIdempotent

Returns the six dimensions and all 30 questions with their numbered answer options (1 = least AI-native, highest number = fully AI-native). Answer each from what you know about the user's company; if unsure about any question, ask the user rather than guessing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint=false, and idempotentHint, so the safety profile is known. The description adds useful behavioral context about how to handle uncertainty ('ask the user rather than guessing') and the meaning of the numeric scale, which helps an agent use the output correctly.

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

Conciseness5/5

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

Two sentences with no filler. The return content is stated first, followed by actionable usage guidance. Every phrase adds value.

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

Completeness5/5

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

There is no output schema, so the description carries the burden of explaining what the agent will receive; it does so by naming the six dimensions, the 30 questions, and the numbered answer scale. For a read-only, zero-parameter retrieval tool, this is sufficient for correct invocation and follow-up behavior.

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

Parameters4/5

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

The tool has zero parameters, so the schema is trivially complete and there is no parameter ambiguity for the description to resolve. The description appropriately focuses on the output content instead of parameters.

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 ('Returns'), a concrete resource ('the six dimensions and all 30 questions'), and clarifies the answer-option semantics. It is distinct from the sibling report, scoring, and email tools because it plainly identifies what is returned.

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

Usage Guidelines4/5

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

The description gives clear operational guidance: answer each question from known company information and ask the user when uncertain. It does not explicitly compare against sibling tools or state when to choose this over alternatives, but the context strongly implies this is the initial assessment-administration tool.

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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