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asset_remove_background

Read-only

Remove background from images to produce transparent RGBA PNGs using AI matting models (BiRefNet, BRIA RMBG, U²-Net) with automatic fallback. Returns the file path.

Instructions

Matte an image to transparent background (BiRefNet / BRIA RMBG / U²-Net via remote endpoint; local white-chroma fallback). Returns RGBA PNG path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesPath or URL to input image
modeNoauto
output_dirNo
Behavior3/5

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

Description adds some behavioral context (remote endpoint, local fallback, returns path). However, annotations declare readOnlyHint=true, while the tool creates an output file (RGBA PNG), which is a write operation. This contradiction reduces transparency. Without annotations, the description would be sufficient, but the mismatch harms credibility.

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?

Single sentence, 20 words, front-loaded with the core action. Every word earns its place—techniques and output format are included without redundancy.

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?

Input schema is simple (3 params, 1 required, no output schema). The description covers the main behavior and return value but omits details about the output_dir parameter and potential side effects. Given the low complexity, a score of 3 reflects adequate but not thorough coverage.

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 33% (only image has a schema description). Description maps mode enum values to algorithm names (BiRefNet, RMBG, U²-Net), adding meaning beyond the enum list. However, output_dir is not explained. Baseline 3 is appropriate since description partially compensates for low coverage.

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 removes background from an image ('matte an image to transparent background') and returns an RGBA PNG path. It references specific algorithms and fallback behaviors, making the purpose unambiguous and distinct from sibling tools like asset_upscale_refine or asset_vectorize.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, limitations, or contrast with similar tools such as asset_generate_logo or asset_sprite_sheet. Usage context is left entirely to the agent's inference.

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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