US Government Open Data MCP

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

No annotations are provided, so the description carries the full burden. It describes what the tool returns and includes constraints (e.g., grade limitations for certain subjects), which adds useful context. However, it doesn't disclose behavioral traits like rate limits, authentication needs, error handling, or pagination. For a read-only data retrieval tool with no annotations, this is a moderate gap.

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 front-loaded with the core purpose, followed by structured bullet-like details (Subjects, Grades, Variables, Jurisdiction). Every sentence adds essential information without waste. It's appropriately sized for an 8-parameter tool with complex constraints.

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's complexity (8 parameters, no output schema, no annotations), the description does well by covering key aspects: purpose, return data, and parameter constraints. It lacks details on output format, error cases, or rate limits, but for a data retrieval tool with rich schema coverage, it's mostly complete. The absence of an output schema is a minor gap.

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 schema already documents all parameters thoroughly. The description adds value by providing high-level semantics: it lists valid subjects, grades, variables, and jurisdictions, and explains constraints (e.g., 'math: 4,8 only; economics/tel/music: 8 or 12 only'). This complements the schema without redundancy, earning a score above the baseline of 3.

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: 'Get NAEP test scores (Nation's Report Card)' with specific details about what it returns ('average scale scores by subject, grade, state, and demographic group'). It distinguishes itself from sibling tools by focusing exclusively on NAEP data, unlike the many other statistical tools (e.g., BEA, BLS, CDC tools) that cover different datasets.

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 listing valid values for parameters (subjects, grades, variables, jurisdictions), which suggests when to use it for NAEP data queries. However, it lacks explicit guidance on when to choose this tool over alternatives (e.g., other education or statistical tools) or any prerequisites/exclusions. The context is clear but not explicitly stated as usage guidelines.

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