list_backends

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only reveals that the tool reports engine status ('which' and 'why'), but does not disclose potential side effects, permissions needed, cost, or response details beyond purpose.

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, concise sentence that is front-loaded and contains no extraneous words. Every part earns its place.

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 (no params, has output schema), and the description adequately states its purpose. However, it could be more precise about what 'why' entails (e.g., context or reason for engine choice). The presence of an output schema reduces the need to describe return values.

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?

With zero parameters and schema coverage 100%, the baseline is 4. The description adds meaning by clarifying that the tool requires no input and reports both the active engine and the reason, effectively compensating for the lack of parameters.

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 uses the specific verb 'report' and clearly identifies the resource ('forecasting engine'). It explains what the tool does (active engine and why), which distinguishes it from siblings 'backtest' and 'forecast' that perform different actions.

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 explicit guidance on when to use versus when not to use. The usage context is implied by the sibling tool names (backtest, forecast), but the description does not state conditions or alternatives, resulting in only implied usage.

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