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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds useful behavioral context by stating the data source ('Audit Analytics public aggregate data'), which informs the agent about data provenance and that data is aggregate rather than company-specific. It does not describe return format, but the core side effects are covered.

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 compact: two functional sentences and one contextual sentence. It front-loads the primary use case, then defines the output, and ends with data source and audience. No redundant words or repeated schema information.

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 read-only benchmark tool with 3 parameters and no output schema, the description covers most essentials: purpose, output metrics, dimension breakdown, and data source. Minor gaps remain, such as the meaning of the 'industry' parameter and how revenue bands are defined, but overall it is sufficiently complete for an agent to invoke it correctly.

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 33% (only annual_revenue_usd is described). The description compensates for two of the three params by explaining that benchmarks are 'by company revenue band and auditor tier', directly mapping to annual_revenue_usd and auditor_tier. However, the 'industry' parameter is left unexplained, and the description does not fully cover the schema's undocumented fields.

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 specifies the tool's purpose: benchmarking audit costs, with concrete output metrics (total fees and fees as a percentage of revenue) broken down by revenue band and auditor tier. It uniquely identifies this as audit-specific among the many benchmark tools in the sibling list, distinguishing it from other get_*_benchmark tools.

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 ('Use when benchmarking audit costs, evaluating auditor proposals, or preparing an audit committee RFP'). It does not mention when not to use it or point to alternatives, but the use cases are clear and contextually sufficient.

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