Mozaika

generate_asset

Generate ON-BRAND icons with AI: subjects (1-12 short nouns, e.g. ["settings gear", "credit card"]) rendered in ONE consistent style. style_from is either a decoded domain ("stripe.com" — the icons match that brand's MEASURED style: accents, stroke, corners) or a house style key ("skeuomorph"). INCLUDED with your account — free accounts get a real daily allowance (enough for a full set), Pro/Lifetime a high one; QA-failed images never count. Returns image_url per subject (1024px transparent PNG) + a zip link.

Input Schema

TableJSON Schema

Name	Required	Default
`format`	No	icon
`subjects`	Yes
`style_from`	Yes

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: it is included with the account with specific allowances for free vs Pro/Lifetime, QA-failed images never count, and it returns image URLs and a zip link. This goes beyond basic expectations and covers operational implications.

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?

The description is a single paragraph of three dense sentences, each adding value: purpose and subjects, style_from explanation, and account/QA/return details. It is somewhat long but contains no filler; front-loaded with the core action.

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?

Given no output schema, the description adequately explains what the tool returns (image_url per subject as 1024px transparent PNG plus a zip link). It also covers usage context, account allowances, and the QA behavior, making it complete for an AI generation tool.

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 schema has no descriptions (0% coverage), so the description compensates by explaining 'subjects' as 1-12 short nouns with concrete examples, and 'style_from' as either a decoded domain or house style key. The 'format' parameter is not explained, but it has a default value and is less critical.

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 generates ON-BRAND icons with AI, specifies the subjects input and the style_from parameter, and differentiates it from sibling tools (which are all get/compare/validate operations). It names the specific resource and action.

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?

The description provides clear context on how to use the tool: subjects should be 1-12 short nouns, and style_from can be a domain or house style key. It also clarifies account-based allowances. However, it does not explicitly state when to use this tool instead of alternatives like get_asset_pack, so no exclusions are given.

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

A3.9/5.0

Disambiguation3/5

The compare_* / get_* / search_* family creates real overlap: compare_components, get_component, get_recipe, and search_screens(kind="component") can all answer similar component questions, and the drift family (get_design_drift, get_design_history, list_design_changes) requires careful reading to pick the right one. However, the detailed descriptions mostly draw clear lines between cross-product comparison, single-spec retrieval, and corpus-level search.

Naming Consistency4/5

The server mostly follows a clean verb_noun convention: get_*, compare_*, list_*, search_*, validate_design, generate_asset. The pattern is highly consistent, though a few names differ slightly in style (audit_code vs validate_design vs get_score), and pluralization varies in tools like compare_components and compare_sections.

Tool Count3/5

At 23 tools this is on the heavy side, and several calls overlap in scope enough to feel redundant. That said, the server's broad purpose suggests a design system reference plus audit platform, so the count is justifiable; it could be consolidated into a tighter 15-18 set.

Completeness4/5

The surface covers design system retrieval, component/section/recipe specs, screens and flows, search, audit/tools, icon assets, and drift/history of measured design tokens, leaving few cap gaps for the declared domain. Minor gaps remain around some metadata like direct screenshot banding by product, but no major dead-end workflow is apparent.

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