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inite-ai

inite-diagnostic

Official
by inite-ai

diagnostic_questions

Ask the eight essential diagnostic questions in order to interview process owners, with industry-specific options in their language. Gather local answers for a complete process audit, identifying bottlenecks and automation opportunities.

Instructions

The eight things a process diagnostic has to establish, in the order they are usually asked. Use them to interview the person yourself — one question at a time, in their language, with options that look like their industry rather than a generic list. Then pass what you collected to read_answers. Runs locally, no account needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral disclosure. It states the tool runs locally and needs no account, which is useful. However, it does not fully clarify what the literal output of invoking the tool is, such as whether it returns a list of questions or a scripted interview guide.

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?

The description is compact and each sentence earns its place: it defines the content, gives practical interviewing guidance, names the next tool, and notes the local execution. It could be slightly tighter, but there is no waste.

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?

Given the tool has no required inputs, no annotations, and no output schema, the description covers the essential workflow: invoke it to get diagnostic questions, conduct the interview, and feed results to read_answers. The only small gap is the absence of explicit detail about the returned format or that the tool itself performs no analysis.

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 Parameter Semantics are not a burden on the description. The schema already confirms there are no inputs, and the description appropriately focuses on how to use the tool's output rather than on parameters.

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 clearly identifies the tool as providing the eight things a process diagnostic must establish, in a defined order. It distinguishes itself from read_answers by stating that this tool is for collecting interview answers while read_answers handles what was collected.

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 concrete usage guidance: interview the person yourself, ask one question at a time, adapt the language and options to their industry, then pass the collected answers to read_answers. It does not explicitly state when not to use the tool, but the workflow is clear.

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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