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Read the account settings

get_account_settings
Read-onlyIdempotent

The settings of the account: the legal name, billing country, postal address and intra-EU VAT number printed on its invoices, plus the language we write to it in and the time zone its hours are shown in. member names the person the language and the time zone belong to. Read it before update_account_settings: the answer gives every setting as it stands, so you change the one the user named and leave the others alone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value beyond these by specifying exactly what data is returned (all account settings) and clarifying the role of 'member' (the person the language and time zone belong to). It also notes the read is a snapshot ('as it stands'), which is useful context for using the result before an update.

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-loading the list of settings and then the usage instruction. Every sentence earns its place: the first defines the resource, the second provides the workflow guidance. No wasted words or padding.

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?

For a no-parameter, read-only tool with an output schema absent, the description fully covers what an agent needs: what the tool returns (all settings), why it exists (to read before updating), and how it relates to sibling update_account_settings. Annotations cover safety, so nothing critical is missing.

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, so the schema provides no parameter details. The description does not need to add parameter meaning, but it does clarify what the output will contain, which is relevant context. Since there are no parameters, the baseline of 4 applies, and the description helps make the tool's purpose and result clear without parameter documentation.

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 the verb 'Read' and the resource 'account settings', then enumerates the specific fields (legal name, billing country, postal address, VAT number, language, time zone, member). It clearly distinguishes itself from the sibling update_account_settings by framing itself as the read step before an update, so an agent can easily tell them apart.

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?

The description explicitly instructs 'Read it before update_account_settings' and explains why: 'the answer gives every setting as it stands, so you change the one the user named and leave the others alone.' This provides clear when-to-use guidance and directly contrasts with the sibling tool, leaving no ambiguity about the intended workflow.

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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TDQS

A4/5.0
Disambiguation4/5

Each tool maps to a distinct resource and action, and the descriptions go out of their way to separate near-neighbor concepts like surfaces vs corroborations and score series vs raw responses. A few related pairs (get_results/get_responses, get_credits/get_usage, create_surface/create_corroboration) could still be confused at a glance, so it is not a perfect 5.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun snake_case pattern across all 67 tools, with clear families like create_, update_, get_, list_, archive_, restore_, and delete_. Minor quirks such as topup_credits as one word do not break the overall uniformity.

Tool Count1/5

67 tools is an extreme count for a single MCP server, even for a broad brand-monitoring domain. The surface is bloated with lifecycle variants per entity, and the sheer number makes the server hard to navigate and prompt against.

Completeness5/5

The server covers full lifecycles for projects, trackers, surfaces, corroborations, quests, logbook entries, keyword discoveries, competitor scans, link targets, sources, support, and billing. Archive/restore and soft-delete paths prevent dead ends, and nearly every obvious workflow has a corresponding tool.

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