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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond that: it emphasizes 'current pricing' (live data), and explicitly rules out side effects like reserving a price, creating a quote, or spending funds. This reinforces the read-only nature and clarifies scope, though it does not describe response format or validation behavior, which are minor gaps given the 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 sentences, zero filler. The positive usage condition is front-loaded, followed immediately by a compact list of exclusions. Every phrase earns its place and no information is repeated from the schema or annotations.

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 complex one-parameter tool with a detailed nested schema and annotations covering safety, the description fully covers invocation context and boundaries. It does not explain the return value or output structure since there is no output schema, but the name and 'current pricing' phrasing make the outcome reasonably inferable. The missing explicit output description is a minor gap, not a fatal one.

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 input schema has 100% description coverage for the single 'proposals' parameter, including nested property documentation with enums and guidance like 'Never infer this from the mode name or another mode.' The description adds only high-level framing ('concrete proposals, mixed models, clip counts, explicit creative attempts') that does not fundamentally extend the schema semantics. Baseline 3 is appropriate because the schema carries the parameter-information burden.

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 opens with a specific verb-resource pairing: 'use this when the user wants current pricing for one or more concrete video production proposals.' It further distinguishes the tool by naming what it is not for—inventing the creative plan, reserving a price, creating a generation quote, inspecting the wallet, or spending funds—which clearly distinguishes it from siblings like prepare_generation, create_topup_link, and get_account_status.

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 explicitly states when to use the tool ('when the user wants current pricing for one or more concrete video production proposals') and provides a clear when-not-to-use list. These exclusions effectively route the agent toward alternatives without needing to name them individually, giving complete usage guidance.

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