sam_get_wage_rates

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

Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral details: it always returns parseConfidence, supports three format options, distinguishes SCA vs DBA, and resolves latest revision via /history. This goes beyond what annotations provide, though it does not cover edge cases like invalid references.

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 a concise paragraph of three sentences, front-loaded with the main purpose. Every sentence adds value: parsing context, SCA/DBA distinction, parseConfidence, format options, and revision resolution. No redundant or unnecessary 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?

The tool has no output schema, but the description provides a high-level picture of what is returned (rate table, parseConfidence, SCA vs DBA). It also explains how to handle low-confidence parsing via raw output. However, it lacks detail on the exact structure of the parsed rates and error handling for invalid references. Overall, it is sufficiently complete for an agent.

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 coverage is 100%, but the description adds substantial meaning beyond the schema. It explains the effect of omitting revision (resolves latest active revision), provides real-world examples for reference (e.g., '2015-4093'), clarifies the default for format ('parsed'), and advises when to use raw format (low parseConfidence).

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 uses a specific verb 'Return' and clearly identifies the resource: 'prevailing-wage + fringe/H&W rate table for a specific wage determination'. It also distinguishes key subtypes (SCA vs DBA) and mentions features like parseConfidence and format options, making it highly specific and unambiguous.

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 provides usage guidance for parameters (e.g., omitting revision resolves latest active revision, using raw format when confidence is low) but does not explicitly state when to use this tool versus sibling tools like sam_search_wage_determinations or gsa_benchmark_labor_rates. The usage context is implied but lacks exclusion criteria.

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