naep_gap_variable_jurisdiction

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering safety. The description adds behavioral context by explaining the return values (innerdiff1, innerdiff2, and the gap), which is helpful but not deep. It doesn't disclose how jurisdictions are ordered (focal vs target) or any data limitations, so it adds moderate value beyond annotations.

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 (three sentences) and front-loads the purpose, then gives a concrete example, and finally outlines outputs. The example is valuable but could be trimmed slightly; still, it is efficient and structured well.

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 is complete for its complexity (5 params, no output schema). It defines the outputs, gives an example, and the schema covers all parameters. Minor gaps like ordering of jurisdictions or handling of multiple years are not critical. Given the annotations and schema, this is adequately complete.

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%, so parameters are fully documented in the schema. The description names the key parameter 'jurisdictions' implicitly via the example and the output fields, but it doesn't add much beyond the schema. It clarifies that the variable must be non-TOTAL with 2+ categories, which aligns with the schema's description, so baseline 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: comparing achievement gaps across states for demographic groups. It uses a concrete example ('Is the poverty gap in math bigger in Mississippi than Massachusetts?') and specifies the output fields (innerdiff1, innerdiff2, and the gap between them), making it distinct from siblings like naep_gap_year_jurisdiction or naep_gap_variable_years which track gaps over time or across years.

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 usage by giving an example, but it does not explicitly state when to use this tool versus alternatives like naep_compare_states or naep_compare_groups. It lacks exclusions or alternative recommendations, so an agent must infer from the tool's focus on cross-jurisdiction gap comparisons.

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