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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the bar for added value is lower. The description goes well beyond this by disclosing the return contents (adjusted amount, cumulative inflation, both index values), the annual data lag and fallback-to-newest-year behavior, and access/pricing constraints. This is strong behavioral disclosure.

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 somewhat long but every sentence carries useful information: purpose, return values, lag behavior, use cases, and access model. The opening question is an engaging lead-in that is quickly followed by the precise statement. It is well structured and front-loaded, though slightly denser than strictly necessary.

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?

With an output schema present, the description does not need to enumerate return fields; it still explains the data source, temporal scope, lag behavior, required input, and authentication model. Nothing an agent needs to call this tool correctly is missing, and the access details (pricing, free tier, no wallet or API key) are especially useful.

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 four parameters with descriptions and defaults. The description adds the required-input reminder ('Required input: from') and clarifies the conceptual direction ('from one year in another year's money'), but it does not add meaning beyond what the schema provides. Baseline 3 is appropriate.

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 concrete, user-facing scenario ('What is 2015 money worth today?') and immediately follows with a precise verb-and-resource statement: 'Restate an amount from one year in another year's money.' It also scopes the tool to World Bank consumer-price series for any country, which clearly distinguishes it from currency-conversion siblings like fx_convert or multi_price.

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 names explicit use cases ('For contract comparisons, historical pricing and long-running budgets') and clarifies behavior for unavailable future years. It does not explicitly name alternatives or say when not to use this tool, but the use-case framing gives an agent enough situational context to select it appropriately.

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