naep_compare_groups

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

The annotations include readOnlyHint=true, so the read-only nature is already known. The description adds behavioral details such as 'significance testing' and 'shows achievement gaps,' which go beyond the annotation and describe what the tool actually does with the data. No contradictions with 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?

Two concise sentences with no fluff. The first sentence states the core purpose, the second provides illustrative examples. Highly efficient and easy to parse.

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?

There is no output schema, so the description must explain what the tool returns. It gives a high-level 'shows achievement gaps' but does not specify the output structure, how significance testing is represented, default values (e.g., year), or behavior with jurisdiction. This leaves some ambiguity for an agent interpreting the results.

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 schema already has 100% coverage, including descriptions for variable ('SDRACE' race gap, 'GENDER' gender gap, etc.) and grade constraints. The description's examples ('White vs Black, Male vs Female') reinforce the variable semantics but do not add significant new parameter-level information beyond what the schema provides.

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 function: 'Compare NAEP scores across demographic groups (race, gender, poverty) with significance testing.' It provides concrete examples (White vs Black, Male vs Female) and differentiates from sibling tools like naep_compare_years and naep_compare_states by focusing specifically on demographic group comparisons.

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 conveys clear usage context by specifying the tool compares demographic groups and shows achievement gaps. It does not explicitly mention alternatives or when not to use the tool, but the examples and phrasing make the intended use case obvious.

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