get_state_lending

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

With no annotations, the description carries the full burden and does a good job: it discloses the default behavior (latest quarter when no period filters), the requirement to supply both from_period and to_period for a series, the FIPS format, and the optional NAICS industry filter. It does not mention auth, rate limits, or error cases, but as a read-only public-data query tool it provides substantial meaningful behavioral context.

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 dense but efficient, packed with useful information across three sentences. It front-loads the purpose and metric list, then gives usage guidance and parameter details. The final source attribution is slightly extra but acceptable for context. It is not overly verbose and avoids repetition.

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 the tool has an output schema and moderate complexity, the description covers most essential context: default behavior, time-series usage, parameter formats, and the public-domain source. The main gap is the unexplained year/quarter parameters and lack of explicit alternative-tool comparisons, but overall it gives enough for an agent to invoke correctly in common scenarios.

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 description adds value by explaining fips (with examples), from_period/to_period format ('YYYY-Qq'), and the NAICS industry filter, which is crucial since schema descriptions are absent for all 6 parameters. However, it completely omits the 'year' and 'quarter' parameters present in the schema, leaving the agent uncertain whether those are alternatives or redundant. This partial coverage lowers the score.

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 a specific verb and resource: 'Get quarterly SBA 7(a) loan aggregates for a single US state' and enumerates the exact metrics returned (loan count, total amount, charge-off rate, average loan size, jobs supported). This distinguishes it from sibling tools like get_county_lending or get_industry_lending by explicitly narrowing scope to state-level SBA loans.

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?

It provides clear usage context: without period filters it returns the latest available quarterly observation, and it instructs to 'Provide both from_period and to_period (YYYY-Qq, e.g. '2024-Q1') for a time series.' While it doesn't explicitly name sibling alternatives or conditions to avoid, the state-specific and SBA-specific framing makes it clear when to select this tool over related ones.

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