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App Icon Generator - Abracadabrax

Prepare App Icon

prepare_app_icon

Prepare an app icon with Abracadabrax for an iOS, Android, web or desktop app: one bold symbol on a rounded square, from what the app does, a symbol idea, a style and the brand colors, with no text. Returns the settings and the credits required; nothing is generated and no credits are spent. No sign-in is needed to prepare. Original designs only: do not use it for copyrighted characters, existing franchises, brand logos, trademarks or real celebrities; offer the user an original alternative instead. Text only: do not use it for uploaded, attached or reference images or videos (editing, background removal, upscaling, image-to-video); for those, point the user to the Abracadabrax workspace.

Input Schema

NameRequiredDescriptionDefault
styleNoflat (default), gradient, 3d or minimal.
colorsNoBrand colors, e.g. electric blue and white.
symbolNoOptional symbol idea, e.g. a running shoe inside a check mark.
model_idNoOptional image model id: nano-banana-2 (default), nano-banana-pro, gpt-image-2.
app_purposeYesWhat the app does, e.g. a habit tracker for runners.

Output Schema

NameRequiredDescriptionDefault
jobNo
stateYes
balanceNo
messageYes
projectYes
dashboard_urlYes
credits_requiredYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Adds real behavior beyond the annotations: no generation, no credits spent, no sign-in required, and a policy constraint that only original designs are allowed. This is exactly the kind of context annotations cannot convey. The only gap is that readOnlyHint=false and idempotentHint=false sit slightly uneasily with 'nothing is generated' — the description never explains what state (if any) the prepare step persists or why repeated calls could differ.

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?

Front-loaded with the core action and output before the negative constraints, which is the right ordering, and every sentence carries a policy or behavioral fact. It is dense and runs long for a description, but the length is driven by genuinely necessary exclusions rather than filler.

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?

With an output schema present, the description need not explain return values, and it uses its space for the things that matter: side-effect profile, auth requirements, creative constraints, and routing to the correct alternative surface. Nothing an agent needs to call this correctly is missing.

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 100%, so the schema already documents all five parameters with examples and defaults. The description restates four of them (app purpose, symbol, style, colors) in prose but omits model_id and adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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?

Specific verb (prepare) plus specific resource (app icon) plus the exact artifact produced ('one bold symbol on a rounded square, from what the app does, a symbol idea, a style and the brand colors, with no text'). It is clearly distinguishable from siblings like generate_media because it explicitly says nothing is generated.

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?

Gives explicit when-to-use and when-not-to-use: text only, not for uploaded/attached/reference images or videos (editing, background removal, upscaling, image-to-video), and routes those cases to the Abracadabrax workspace. It also states the copyright/trademark exclusion (characters, franchises, logos, celebrities) and prescribes the correct fallback behavior (offer an original alternative).

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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