unload_models

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

No annotations are provided, so the description carries the full load; it does disclose a genuine behavioral trait — models are unloaded and must be reloaded on the next call, which signals latency cost. It does not say whether this interrupts in-flight work, what happens if nothing is loaded, or what the call returns.

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?

One sentence, action front-loaded, with the reload consequence in a parenthetical that earns its space by warning about the cost of calling it. No filler.

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 zero-parameter, no-output-schema utility tool, the description covers what it does and the main side effect (reload on next call). Minor gaps remain around whether in-flight generation is affected and what the response contains.

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; baseline 4 applies. The description correctly avoids inventing options that the empty schema does not support.

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?

Specific verb + resource combination ('free the memory held by the loaded models') that an agent can map directly to a resource-management action. It reads as unambiguously distinct from the audio-processing siblings, though it never names them explicitly.

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 word 'now' and the parenthetical about reloading imply this is a memory-pressure action taken between calls, but there is no explicit when-to-use guidance, no exclusion (e.g., mid-generation), and no mention of alternatives.

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