Skip to main content
Glama

Update Ai Preferences Tool

update-ai-preferences

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

A4.6/5.0
Behavior4/5

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

The description labels the action as 'state-changing', which aligns with readOnlyHint=false. It adds context beyond the annotations by mentioning authorization requirements and the possibility that team-enforced settings can prevent member edits, but does not detail success/failure side effects.

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, front-loaded with the primary use case, and lists the changing fields succinctly. No unnecessary fluff.

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?

Covers the key context (authorization, team enforcement, scope) and the main purpose. Lacks details about successful update behavior (e.g., return value) but that is not required given no output schema. The description is sufficient for an agent to decide whether to invoke 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?

All 6 parameters have descriptions with some added constraints (e.g., max lengths, permission context, scope). However, 'apply_to_generators' is described only as 'GenerationType integer values', which is vague without a reference to what GenerationType means, and there is no clarification that all fields are optional in a patch-like update.

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 clearly states the tool's purpose: changing AI writing guidelines, templates, strict mode, generator scope, or team enforcement. It uses a specific verb ('change') and resource (AI preferences), and implicitly distinguishes from the read-only sibling get-ai-preferences.

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

Usage Guidelines5/5

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

Explicitly states when to use it ('Use this when the user wants to change...') and includes important caveats about authorization and team-enforced settings preventing member edits. This gives clear guidance for choosing this tool over alternatives.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources