list_available_models

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

With no annotations, the description carries the full behavioral burden, yet it discloses nothing about failure modes when a local service is down, whether results are cached, latency, or whether the call is read-only and side-effect free. 'Across local services' is the only behavioral signal offered.

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 five-word sentence with no padding, and the scope qualifier is placed front and center where an agent will read it first.

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 low-complexity and an output schema exists, so return values need not be explained. However, against a sibling set crowded with overlapping list_* tools, the description is too thin to route the agent correctly, and with no annotations it leaves the safety and failure profile unspecified.

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, so there is nothing for the description to disambiguate beyond what the empty schema already conveys. Baseline 4 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?

The verb+resource pair is clear ('List models') and the scope qualifier 'across local services' hints at aggregation, but it never distinguishes itself from the many provider-specific siblings such as list_mlx_models, list_llamacpp_models, and list_nexus_models. An agent cannot confidently tell whether this is a superset or a distinct third thing 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?

There is no when-to-use statement, no when-not-to-use, and no named alternative among the four or more sibling listing tools. The agent is left to infer routing entirely on its own.

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