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mtbun

storeshots-mcp

by mtbun

generate_set

Batch-convert raw app screenshots into pixel-perfect store listing visuals with device frames, brand colors, and platform-preset dimensions.

Instructions

Batch-renders an ordered screenshot set for one preset and language. Item N becomes {lang}_{NN}.png. Returns per-item results plus any warnings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoBCP-47 language code for locale-aware uppercasing, e.g. "en", "tr", "de"en
itemsYesOrdered list of screenshots to render
presetYesPlatform preset id
outputDirYesDirectory for the set; files are named {lang}_{nn}.png in item order
backgroundYesBrand background color as 6-digit hex, e.g. "#E31837"
noGradientNo
Behavior3/5

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

With no annotations, the description carries the full burden. It mentions file naming convention and return format (per-item results plus warnings), but does not disclose that files are written to disk, whether it overwrites existing files, or potential side effects like directory creation. The behavioral traits are partially transparent but have gaps.

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 consists of two concise sentences. The first sentence clearly states the tool's purpose, and the second provides essential details about output naming and return value. No redundant information, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters (including nested items array) and no output schema, the description explains output format but omits important context such as error handling (e.g., partial failures), whether outputDir must pre-exist, and the structure of per-item results. It is adequate but not fully complete for a complex batch operation.

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 description coverage is high (83%), so the baseline is 3. The description adds value by explaining the naming pattern '{lang}_{NN}.png', which ties the 'lang' parameter to output filenames. However, it does not elaborate on other parameters like 'background' or 'noGradient' beyond what the schema already provides.

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 verb 'batch-renders' and the resource 'ordered screenshot set for one preset and language'. It distinguishes itself from sibling tools like 'compose_screenshot' (single screenshot) and 'list_presets' (listing), making its unique purpose unambiguous.

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 implies batch rendering of multiple screenshots, but does not explicitly state when to use this tool vs alternatives (e.g., when to choose 'generate_set' over 'compose_screenshot' or 'validate_screenshot'). No exclusion criteria or prerequisites are mentioned, leaving usage context somewhat vague.

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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