models

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

No annotations are provided, so the description carries the full burden. It mentions API key requirements for setting models, which is useful, but lacks details on behavioral traits such as whether changes are persistent, if there are rate limits, error handling, or what happens when configurations are set (e.g., immediate effect vs. requires restart). For a tool with 10 parameters and no annotations, this is a significant gap in transparency.

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 appropriately sized with two sentences that are front-loaded: the first states the dual purpose, and the second provides specific usage guidance. There is no wasted text, making it efficient, though it could be slightly more structured to separate the 'get' and 'set' functionalities more clearly.

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?

Given the complexity (10 parameters, no output schema, no annotations), the description is incomplete. It covers basic purpose and a usage scenario but lacks details on return values, error conditions, or how the tool integrates with the broader system (e.g., sibling tools). This makes it adequate but with clear gaps for a tool of this scope.

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%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema, as it does not explain parameter interactions or provide additional context like how 'listAvailableModels' relates to 'setMain' or 'setFallback.' Baseline 3 is appropriate when the schema does the heavy lifting.

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 states the tool 'Get information about available AI models or set model configurations,' which provides a general purpose but lacks specificity about what 'set model configurations' entails. It distinguishes from siblings by focusing on models rather than tasks or dependencies, but the dual purpose (get info vs. set configs) makes it somewhat vague compared to more focused sibling tools.

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 clear context: 'Run without arguments to get the current model configuration and API key status for the selected model providers.' This gives explicit guidance on when to use it in a no-argument scenario. However, it does not specify when to use it versus alternatives (e.g., which sibling tools might interact with models) or when not to use it, keeping it from a score of 5.

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