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priority_audit_from_text

Read-only

Analyzes service request descriptions against their current priority, flagging requests where the urgency in the text doesn't match the assigned priority. Also flags requests whose description is too vague or empty to dispatch a technician on. Returns each flagged request with the issue found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description usefully adds what counts as a flag (urgency mismatch, vague/empty description) and the shape of the result. However it says nothing about the scope of requests scanned, whether any limit/cap applies, or whether the check is deterministic versus model-based — notable gaps for a zero-parameter audit tool.

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?

Three sentences, front-loaded with the core behavior, and the return value is stated last. Efficient, though the second clause ('also flags requests whose description is too vague or empty') slightly repeats the flagging frame and could be tightened.

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 input schema, no output schema, and annotations covering safety, the description carries the burden well by explaining both trigger conditions and the result shape. The one missing piece is scope — which requests are evaluated and over what period — which an agent cannot infer from any structured field.

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 takes zero parameters, so the baseline of 4 applies. There is nothing for the description to disambiguate, and it does not introduce unnamed inputs.

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?

States a specific action (analyzes service request descriptions against assigned priority) plus the two flagging conditions, and describes the return payload. No sibling tool performs a priority-vs-text audit, so it is clearly distinguishable from the surrounding analytics and listing tools.

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

Usage Guidelines3/5

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

The scenario where this tool pays off is implied by the description (auditing priority consistency), but there is no explicit when-to-use statement, no mention of prerequisites, and no routing away from alternatives such as overdue_tasks, rework_check, or the various list_* tools. Usage is inferable rather than stated.

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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