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Evaluate a state against custom typed questions to return probability, choice, or score judgments for text, drafts, or note pairs.

Instructions

Low-level access: evaluate a state against your own typed questions. Question types: {"type":"noul","instructions":"..."} (probability 0-1), {"type":"choice","instructions":"...","criteria":{"key":"description"}} and {"type":"score","instructions":"...","criteria":["level 0","level 1"]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYesThe text or situation to judge
questionsYesMap of question name to question object

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds the phrase 'low-level access' but does not disclose side effects, rate limits, or result format beyond what annotations provide.

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 front-loads the core action before listing question types. It is dense but every sentence earns its place, with only minor jargon in 'Low-level access.'

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

Completeness3/5

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

Given nested object parameters and no output schema, the description thoroughly documents input shapes but says nothing about what the tool returns or how evaluation results are formatted. That omission leaves an agent uncertain about the response format.

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

Parameters5/5

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

Although schema description coverage is 100%, the input schema only describes the questions parameter as a generic object map with additionalProperties: {}. The description compensates by defining three explicit question type structures (noul, choice, score) with their fields and value types, adding substantial meaning not present in the schema.

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 states a specific verb and resource: 'evaluate a state against your own typed questions.' It distinguishes the tool as a low-level evaluation primitive, but does not differentiate it from siblings, which appear unrelated.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. There are no exclusions or prerequisites mentioned, leaving usage entirely to inference.

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