sba_size_standard

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

The description discloses key behavioral traits beyond annotations: the dataset lacks an effective date, so the result is timestamped with asOf; it clearly states that SBA adjusts standards periodically and advises re-verification. It also ensures no fabricated results for unknown NAICS. Annotations (readOnlyHint, openWorldHint) are consistent and not contradicted.

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 informative and well-structured, front-loading the core purpose. It uses clear labeling like 'HONESTY:' to highlight caveats. While every sentence adds value, the description could be slightly more concise without losing essential details.

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?

Given no output schema, the description thoroughly explains the return fields (standardType, threshold, unit, footnote) and the honesty note about data freshness. It also covers error handling for unknown NAICS. This is complete for a simple lookup tool with one parameter.

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 covers 100% of parameters with a clear description of the naics parameter ('6-digit NAICS code'). The tool description adds minimal new meaning beyond the schema, merely restating the format. With high schema coverage, a baseline of 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 clearly states the tool's purpose: to look up the SBA small-business size standard for a 6-digit NAICS, specifically answering 'is a firm SMALL for this NAICS?' and acting as a gate for set-aside eligibility and vetting teaming partners. This distinguishes it from sibling tools that deal with contracts, agencies, or other government data.

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 this tool (for set-aside eligibility and vetting candidates) and provides important caveats: the dataset has no effective-date field, so values are 'as of retrieval' and SBA adjusts standards periodically, recommending re-verification at sba.gov for high-stakes decisions. It also notes that unknown NAICS return found:false, avoiding fabricated results.

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