image_remove_bg_auto

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

With no annotations, the description carries the full behavioral burden. It hints at the algorithm ('analyzing edges') but says nothing about whether the operation is destructive, reversible, undoable, or dependent on image content, all of which matter for a mutating layer tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single tight sentence with the core action front-loaded and zero filler. It is efficient, though brevity here borders on under-specification.

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

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

For a one-parameter mutation tool with no annotations and no output schema, the description covers the action and method but omits behavioral essentials (reversibility, failure modes) and the sibling distinction. Adequate but with clear gaps.

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

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

Schema description coverage is 100% and the single layerId parameter is already documented in the schema. The description adds no additional meaning about the parameter (e.g. whether the layer must be a raster image), so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('background removal to an image layer') and adds method detail ('by analyzing edges'). However, it never distinguishes itself from the sibling image_remove_bg_magic, so an agent cannot tell which background-removal tool to pick without guessing.

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

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

No when-to-use guidance, no prerequisites, and no mention of image_remove_bg_magic as the alternative. The 'auto' vs 'magic' naming implies a distinction the description never resolves, leaving selection to inference.

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