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Update Ai Preferences Tool

update-ai-preferences
Destructive

Use this when the user wants to change AI writing guidelines, templates, strict mode, generator scope, or team enforcement. After authorization, this state-changing action updates personal or owner-managed team preferences; team-enforced settings can prevent member edits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
template_textNoMarkdown template, max 12000 characters.
guidelines_textNoText guidelines, max 4000 characters.
strict_templateNoStrict template mode.
enforce_for_teamNoTeam-owner-only enforcement flag.
use_team_settingsNoPreference scope to update: personal or team. Team scope requires owner authorization.
apply_to_generatorsNoGenerationType integer values.

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?

With annotations already declaring destructiveHint=true and readOnlyHint=false, the description adds meaningful behavioral context: authorization is required, the action is state-changing, updates may apply to personal or owner-managed team preferences, and team enforcement can block member edits. It still does not state whether omitted fields are left unchanged or reset, which is relevant for an update tool.

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 usage trigger and then the behavioral constraints. Every clause earns its place and there is no filler.

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

Completeness4/5

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

For a six-parameter mutation tool with no output schema, the description supplies the key auth and team-enforcement context that annotations and schema do not. The main remaining gap is that it does not clarify partial-update semantics when all parameters are optional.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already defines all six parameters with types and constraints. The description's field list largely duplicates the schema's parameter set without adding new syntax, formats, or default behavior.

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 ('change/update') and resource ('AI writing guidelines, templates, strict mode, generator scope, or team enforcement'), and the scope distinguishes it from the read-only sibling get-ai-preferences. An agent can identify exactly what this tool mutates 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 gives a clear trigger: 'Use this when the user wants to change...' and adds the important condition that team-enforced settings can prevent member edits. It does not explicitly name get-ai-preferences as the alternative for reading preferences, so it stops short of full when/when-not/alternatives guidance.

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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