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aaddyy_product_photo_studio

Transform casual product images into professional e-commerce photos. AI analysis selects themes and generates multi-angle shots with optional feature highlights.

Instructions

Generate professional e-commerce product photos from casual uploads. AI-powered analysis, theme selection, and multi-angle photo generation with optional feature highlights. (~20 credits)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
themeNoai_recommended
num_outputsNo
product_nameNo
product_imagesYes
product_categoryNo
feature_highlightsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It usefully discloses the pipeline (AI analysis, theme selection, multi-angle generation) and a cost signal (~20 credits), but omits processing time, output format, auth needs, and whether the source images are modified or retained.

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 compact sentences that lead with the core purpose and append the capability and cost details. No filler, though the middle sentence is a feature list rather than information an agent needs to call the tool.

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

Completeness2/5

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

For a 6-parameter, unannotated tool with no output schema, the description is thin: several parameters are unexplained and there is no guidance on outputs, limits, or failure modes. Adequate only as a high-level pitch.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 6 parameters, so the description must compensate. It only loosely gestures at theme and feature_highlights and never explains product_name, product_category, or the num_outputs default of 5, leaving most parameters undocumented in both places.

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 (Generate) and resource (professional e-commerce product photos) plus the input type (casual uploads), which distinguishes it from siblings like aaddyy_image_generator or aaddyy_background_remover. Clear but does not explicitly name a sibling alternative to contrast against.

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

Usage Guidelines2/5

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

Gives an implied use case ('from casual uploads') but never says when to choose this over the many other image tools in the sibling list, nor any prerequisites. No exclusions or alternatives are named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.