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

Annotations cover the safety profile (readOnlyHint, idempotentHint, openWorldHint), yet the description still adds non-obvious traits: no credits are spent, results are cached ~1 minute server-side, and at least one connected Google account is required. It also describes the partial-failure shape ({statuses: ... {"error": ...}}).

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?

Front-loaded with the value proposition and the routing hint, then scoping and return shape. Slightly padded by the 'READ-ONLY: nothing is generated and no credits are spent' line, which partly restates the annotations, but every sentence still carries useful content.

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?

No output schema exists, but the description still sketches the return object and the account/auth prerequisite, plus cache behavior and the failure branch. Nothing an agent needs to call this correctly is missing.

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 no per-parameter semantics to document; the description correctly spends its words on behavior instead. Baseline for 0 params is 4.

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?

States a specific verb+resource (reads Google Flow's live model catalog with usage keys, prices, durations) and explicitly distinguishes itself from the sibling list_models, which returns the curated accepted-id list. The agent can route correctly without opening either schema.

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?

Gives explicit when-to-use framing ('use to answer is this model still working?'), names the alternative ('Use list_models instead for the short curated list of ids'), and states the selecting condition ('use this one when you need Google's ground truth'). No inference required.

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