naep_gap_year_jurisdiction

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds value by disclosing the return elements (innerdiff1, innerdiff2, and the gap), which are not visible from the schema. It could be stronger about edge cases, like jurisdiction ordering or multi-jurisdiction behavior.

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 definition is compact: purpose in the first sentence, a concrete example second, and a return-value explanation third. No redundant 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 tool with 5 parameters and no output schema, the description does a good job covering the interpretative layer (what the output means). Remaining gaps are minor: it does not explain how multiple jurisdictions beyond two are processed or what exactly 'focal' refers to in the parameter order.

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 100%, so the baseline is 3. The description adds helpful conceptual language (focal vs. target jurisdiction) but does not map those concepts to specific parameter positions or add details beyond the schema.

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 states a clear action — compare how score changes between years differ across jurisdictions — and provides a concrete real-world example. It does not explicitly name sibling tools to disambiguate, so it falls slightly short of full sibling differentiation.

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 example ('Did the COVID learning loss hit California harder than Massachusetts?') gives clear contextual guidance on when to use the tool. It does not explicitly mention when-not-to-use it or offer alternative tool names, keeping it below a 5.

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