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

Annotations already indicate read-only, open-world, and idempotent behavior. The description adds that the output includes data sources and warnings, which is useful but does not disclose detailed behavioral traits (e.g., data freshness, handling of missing data, or rate limits).

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 concise (3 sentences, ~40 words) and front-loads the action. It avoids redundancy, though a more structured format (e.g., listing inputs) could improve scannability.

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 description covers core functionality and touches on output contents, but given the existence of sibling tools and a moderate parameter count, it lacks details on optional parameters (targetYear) and data freshness. With output schema present, return value details are less critical, but completeness is still average.

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 only 20% (only 'async' described). The tool description mentions 'country codes, base salary, and reference year' but does not explain the purpose of 'targetYear' or provide details on formats, defaults, or constraints beyond what the schema types imply. This is insufficient to compensate for the low schema coverage.

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 clearly states the tool adjusts salary benchmarks for local inflation using OECD, IMF, and World Bank data. It identifies the target user (CHROs) and the goal (normalize compensation across regions). However, it does not differentiate from sibling compensation tools like 'comp_benchmark_geo_delta' or 'executive_comp_peer_benchmark'.

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 implies use for inflation adjustment of salary benchmarks, but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The context of sibling compensation tools suggests a need for clearer differentiation.

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