list_background_models

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

With no annotations, the description carries the full burden. It discloses that the tool returns a dictionary with a models list and default model information, which gives some insight into the output. However, it does not explicitly state that this is a read-only operation, nor does it mention any side effects or performance implications. For a listing tool, this is acceptable but not rich.

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?

The description is concise with three sentences. The first sentence states the core purpose, the second adds detail, and the third specifies the return type. It is front-loaded and contains no filler, though the final sentence about returns might be redundant given the output schema exists, but it does not hurt.

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?

The tool is simple with no parameters and an output schema. The description covers what the tool does (lists models) and what the output contains (models with descriptions, use cases, and default info). This is sufficient for an agent to know when to call it and what to expect. There is no obvious missing context for this basic listing operation.

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?

The tool has zero parameters, so the description does not need to explain any. Baseline for 0 parameters is 4, and the description appropriately focuses on the output rather than input. No parameter-related information is missing.

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?

The description clearly states the verb 'List' and the resource 'all available background removal models', which is distinct from sibling tools like remove_background (which likely removes) and unload_models (which unloads). It also specifies that it returns descriptions and recommended use cases, making its purpose unambiguous.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios where this tool is appropriate or when to avoid it, nor does it reference sibling tools. The only implicit context is that it lists models, but no explicit routing or exclusions are given.

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