LLM Red-Team Scanner

validate

Judge one delivery against the task's own acceptance rule and return {verdict: accepted|rejected, reason}. Called by the brick.blue hub when this seat is drawn as validator. Judges only machine-checkable criteria (json_schema / contains / fields); a task with no such rule is accepted, because rejecting needs evidence.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "validate"
  }
}

Input Schema

Name	Required	Description	Default
`input`	No
`title`	No
`result`	No
`taskId`	No
`attemptId`	No
`description`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 30, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the judging criteria (json_schema / contains / fields), the default acceptance behavior, and the return shape, but it does not state whether the tool is read-only, whether it records anything, or what permissions are required.

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?

The description is two dense sentences with the core action and return shape front-loaded. Every clause adds useful information about purpose, invocation, or judgment policy.

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

Completeness2/5

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

The description explains purpose, invocation context, and return value, which is helpful. However, for a six-parameter tool with 0% schema description coverage and no annotations, it leaves parameter usage and operational side effects undocumented, so it is not complete enough for reliable invocation.

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

Parameters2/5

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

Schema description coverage is 0% across six parameters, so the description must compensate. It hints at a delivery and a task acceptance rule, but does not map meaning to input, result, taskId, attemptId, title, or description.

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 and resource: 'Judge one delivery against the task's own acceptance rule.' It also specifies the return shape and the validator context, so an agent can tell exactly what this tool does without opening the schema.

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?

It explains that the brick.blue hub calls this tool when the seat is drawn as validator, which is clear situational guidance. It also states the acceptance policy for tasks without machine-checkable rules, but it does not name any alternative tools or exclusions.

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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