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callingly

Change account settings

update_settings
Idempotent

Change settings on one record (the account, a team, an AI agent or a user). Use the exact field names from get_settings, and put only the fields that change in changes; several changes to the same record go in one call. Returns what was saved, or validation errors (in which case nothing was saved — fix the values or explain the problem).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoRecord id (not needed for the account).
entityYes
changesYesField name → new value, for the fields that change only. Booleans as true/false; lists (questions, qualification_questions, retry_schedule) as the full new list.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover idempotence and non-destructiveness, and the description adds genuinely new behavior: it returns what was saved, and on validation errors nothing is persisted. That failure-atomicity detail is exactly the kind of context the annotations do not supply.

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?

A single dense paragraph, front-loaded with the operation and scope, followed by the read-first prerequisite, the batching rule, and the return/error contract. Every clause carries functional information with no padding.

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 nested-object mutation with no output schema, the description supplies the prerequisite lookup, payload discipline, batching, and the success/failure outcome, which is enough to call it correctly. It leaves the semantics of individual settings fields to get_settings, which is a reasonable handoff.

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 coverage is 67% and the schema already documents the changes payload format (booleans, full replacement lists) and that id is unneeded for the account. The description's main addition is the instruction to reuse exact field names from get_settings, which is useful but overlaps heavily with the schema text.

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?

States a specific verb (change) plus the resource (settings) and enumerates the four record types it can target (account, team, AI agent, user), which mirrors the entity enum. It does not, however, distinguish itself from overlapping siblings such as manage_user, manage_team, manage_ai_agent, or update_team_members, so an agent still has to infer whether those handle different concerns.

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?

Gives real operational guidance: read field names from get_settings first, send only changed fields, and batch multiple changes to the same record into one call. It stops short of stating when NOT to use this tool or which sibling to prefer for non-settings mutations.

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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