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Get Ai Preferences Tool

get-ai-preferences
Read-only

Use this when the user wants to view current AI writing guidelines, templates, strict mode, generator scope, or team-enforced generation preferences. Read-only: returns effective personal/team preferences and whether they are editable without changing settings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already establishes safety, and the description reinforces it by stating 'Read-only' and clarifying that it returns preferences 'without changing settings.' It adds useful context about the return value being effective personal/team preferences and editability, going slightly beyond the bare annotation.

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 sentences with zero wasted words, front-loaded with the 'Use this when...' trigger. Every clause earns its place, covering purpose, side-effect profile, and return semantics efficiently.

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?

There is no output schema, but the description covers the return content ('returns effective personal/team preferences and whether they are editable'). For a simple parameterless read tool, this is complete: the agent knows when to call it, what it does, and what it returns.

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 has zero parameters and an empty schema, so there is nothing to document. Per the baseline for 0 params with full schema coverage, the score is 4.

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 ('view') and specific resources ('AI writing guidelines, templates, strict mode, generator scope, or team-enforced generation preferences'), making the purpose clear. It distinguishes itself from sibling tools implicitly through the read verb contrasting with update-ai-preferences, though it does not explicitly name any alternative.

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 an explicit trigger condition ('Use this when the user wants to view current...preferences') that tells the agent when to invoke this tool. It does not explicitly contrast with update-ai-preferences or other siblings, but the read-versus-write boundary is reasonably clear from the wording.

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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