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remove_background

Read-onlyIdempotent

Remove image background using AI (U2-Net). Returns RGBA PNG/WebP with transparent background. Perfect for product photos, portraits, and design assets. FREE. (FREE)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesBase64-encoded PNG/JPEG image
output_formatNoOutput formatpng

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety profile is clear. Description adds model name (U2-Net) and output format but no additional behavioral traits like rate limits or auth needs.

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?

Two concise sentences covering purpose, output, and use cases. The repeated 'FREE' is slightly redundant but does not harm clarity. Front-loaded with key information.

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?

For a simple two-parameter tool with no output schema and supportive annotations, the description covers the main behavioral aspects (output format, use cases, free status). Lacks only minor details like image format restrictions for input (but schema covers base64).

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% with clear descriptions for both parameters (image base64, output_format enum). The description does not add further meaning beyond what the schema provides, meeting the baseline but adding no extra value.

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?

Clearly states the action (remove background), technology (U2-Net), and output (RGBA PNG/WebP with transparency). Provides use cases (product photos, portraits, design assets) that distinguish it from sibling tools like resize_image or upscale_image.

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?

Explicitly mentions ideal use cases (product photos, portraits, design assets) giving clear when-to-use guidance. Does not mention alternatives or when not to use, but sibling tool names imply other image operations.

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

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct operation—artwork retrieval, image processing, asset management, watermarking, etc.—with clear descriptions that prevent confusion. Even similar tools like enrich_metadata and get_artwork_oracle are differentiated by depth and purpose.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern in snake_case (e.g., get_artwork, remove_background, register_hash). The few non-verb-starting names (compliance_manifest) are standard and do not break the overall pattern.

Tool Count4/5

27 tools is slightly above the typical range but justifiable given the broad domain covering artwork access, image processing, and digital rights. Each tool serves a unique purpose without redundancy.

Completeness5/5

The tool set covers the full lifecycle: search, retrieve, analyze, edit, save, and verify assets. Gaps are minimal—e.g., no metadata deletion tool—but the core workflows are fully supported, and the inclusion of compliance and provenance tools adds value.