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unreal_validation_rules

Read-only

List project-approved native Data Validation rules and their availability, shown only when configured in JevEditor.Validation policy.

Instructions

List named project-approved native Data Validation rules and their availability.

Disabled unless explicitly configured in the project's [JevEditor.Validation] policy. Only loaded native validator classes are eligible; no Blueprint/Python rule discovery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already mark the tool readOnly and non-destructive. The description adds important non-schema behavior: the tool is disabled unless project policy enables it, and only loaded native validator classes are eligible, so results are not exhaustive across all possible rules.

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?

Three short, purposeful sentences lead with the core purpose, then add the two most important constraints. No filler or repetition of schema/annotation information.

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?

For a parameterless listing tool with an output schema, the description provides the purpose and the key eligibility/availability constraints. Nothing else is needed for an agent to decide whether and how to call it.

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 there is no parameter meaning for the description to add. The schema coverage is complete and the baseline of 4 applies.

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 opens with a specific verb+resource: 'List named project-approved native Data Validation rules and their availability.' This clearly distinguishes the tool from sibling validation/workflow tools by scoping to rule discovery rather than executing or inspecting jobs.

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 context: the tool lists project-approved native rules only, and it explicitly excludes Blueprint/Python rule discovery. It does not name alternative sibling tools for those cases, but the scope constraints make the appropriate use case clear.

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