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Generate logo concepts

generate_logo

Generate AI logo concepts (icon + palette + typography + layout) for a business. Returns N variations. Requires Founder sub or one-time LOGO_PACK/BRAND_KIT purchase. [Requires a free namemy.app API key — get one at https://namemy.app/app/api-keys]

Input Schema

NameRequiredDescriptionDefault
nameYes
countNoNumber of variations (1-9)
sloganNo
descriptionYesWhat the business does
preferencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, openWorldHint=false, so the safety profile is known. The description adds meaningful non-structured context: paid entitlement gating (Founder sub or one-time pack) and an external API-key requirement with a URL, which the agent needs before invoking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences with the core action front-loaded, followed by output and then prerequisites. The bracketed API-key note earns its place, though the paid-tier and API-key sentences could be merged into one prerequisite clause.

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?

With no output schema, the description carries the return-value burden and does state the shape (N variations of icon/palette/typography/layout) plus access prerequisites. The main gap is the undocumented nested preferences object, which is not addressed anywhere.

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 only 40%, so the description must compensate. It hints at the business context (name/description) and that count drives the number of variations, but it says nothing about the nested 'preferences' object (styles, industry, colorPalette) or the slogan, leaving the most complex parameter undocumented.

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 and resource ('Generate AI logo concepts (icon + palette + typography + layout) for a business') and the output shape ('Returns N variations'). It is distinguishable from brand_conflict_check or buy_domain, but it does not explicitly differentiate itself from the adjacent sibling generate_brand_kit, whose component list sounds similar.

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

Usage Guidelines3/5

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

The description gives clear prerequisites (Founder subscription or one-time LOGO_PACK/BRAND_KIT purchase, plus a free API key) but no guidance on when to pick this over generate_brand_kit or generate_names. Usage is implied by the purpose rather than routed.

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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