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

Annotations already cover read-only/idempotent/destructive safety. The description adds valuable behavioral context: it returns the result, serving model, and exact cost, and requires a Flow AI API key in the Authorization header. This goes beyond the schema and annotations.

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?

Two tight sentences, with the primary purpose and benefit front-loaded, followed by return value and authentication requirement. Every sentence earns its place with 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 5-parameter tool with no output schema, the description covers the essential behaviors: what is delegated, what is returned, and what auth is needed. It could mention error cases or model-selection behavior in more detail, but the current information is sufficient for correct invocation in most cases.

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 baseline is 3. The description does not add parameter-level syntax or format details beyond what the schema already provides, but it does reinforce the overall cost-saving intent that ties the parameters together.

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 a specific verb ('Hand … to the cheapest model') and identifies the exact resource and intent: offloading a self-contained subtask. It clearly distinguishes itself from the sibling bus/council/search tools by focusing on cost-saving delegation.

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 gives clear applicability criteria: use it for self-contained subtasks that don't require your own expensive model, to save tokens and move faster. It does not name explicit alternatives or exclusion cases, but the context is strong enough for an agent to decide when to invoke it.

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