list_models

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only enumeration but says nothing about ordering, scope (all models vs. working directory), pagination, or what 'saved' excludes, all of which matter for an enumeration tool with zero annotation coverage.

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 four-word sentence is front-loaded and waste-free, but it is terse to the point of under-specification rather than efficient conciseness. Nothing is padded, yet nothing beyond the bare minimum is stated.

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 output schema means return values need no explanation, and with zero parameters the surface area is small. Still, with no annotations an agent gets no confirmation of read-only safety or the scope of 'saved' models, leaving the description just barely adequate.

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 takes zero parameters and the description introduces none, so there is no parameter semantics to misrepresent. Baseline 4 applies for a no-parameter tool.

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 (List) and resource (saved models), which is enough to distinguish it from siblings like list_parts and list_colors by resource type. However, it doesn't clarify what 'saved' means versus unsaved/in-memory models, which matters given siblings like new_model and open_model.

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 guidance on when to use this versus open_model, check_model, or describe_model, nor any prerequisite or context. The agent must infer usage purely from the verb 'List'.

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