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lint_requirements

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Run deterministic quality checks on requirements to find missing acceptance criteria, vague wording, and compound statements.

Instructions

Deterministic requirement quality checks (missing acceptance criteria, vague words, compound requirements). Judging ambiguity and conflicts is your job: use flag_requirement_issue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already establish the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the burden is low. The description adds genuinely useful behavioral context by declaring the checks are deterministic, which tells the agent results are reproducible and rule-based rather than judged. It does not discuss result volume or ordering, but that is minor here.

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, front-loaded with the tool's function, followed immediately by the routing guidance. No filler and no repetition of the schema or annotations.

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?

An output schema exists, so return values need no explanation, and the safety profile is covered by annotations. With zero parameters and a clearly stated scope plus an explicit hand-off to flag_requirement_issue, nothing an agent needs to select or invoke this tool is missing.

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 per the baseline this scores 4. The description adds nothing parameter-related because there is nothing to document, and the empty schema is unambiguous (it presumably operates over the current requirement set).

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 verb and resource ('requirement quality checks') and enumerates the concrete check classes (missing acceptance criteria, vague words, compound requirements). It also explicitly distinguishes itself from flag_requirement_issue, so an agent can separate the two without opening either schema.

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?

Explicit boundary routing: this tool covers deterministic checks, while 'Judging ambiguity and conflicts is your job: use flag_requirement_issue.' This tells the agent both when to use this tool and which sibling to use instead for the excluded case.

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