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 of behavioral disclosure. It mentions the return values ('innerdiff1', 'innerdiff2', and the gap between them'), which adds some context about output structure. However, it does not disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, error conditions, or data freshness. For a tool with no annotations, this leaves significant gaps in understanding its 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 description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by an example and return value details. Every sentence adds value without redundancy. It could be slightly more structured (e.g., bullet points for returns), but it remains 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?

Given the complexity (comparing jurisdictional gaps in year-over-year score changes) and the absence of both annotations and an output schema, the description is moderately complete. It explains the purpose, provides an example, and outlines return values, which helps compensate for the lack of structured output details. However, it does not fully address behavioral aspects or error handling, leaving room for improvement in completeness.

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 description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description does not add any additional meaning or examples beyond what the schema provides (e.g., it doesn't clarify parameter interactions or typical values). According to the rules, with high schema coverage, the baseline is 3 even with no param info in the description.

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: 'Compare how score changes between years differ across jurisdictions.' It specifies the verb ('compare'), resource ('score changes'), and scope ('across jurisdictions'), and distinguishes it from sibling tools like 'naep_compare_years' or 'naep_compare_states' by focusing on jurisdictional differences in year-over-year changes.

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 provides an example ('Did the COVID learning loss hit California harder than Massachusetts?') that implies usage for comparing learning impacts across jurisdictions. However, it does not explicitly state when to use this tool versus alternatives like 'naep_compare_states' or 'naep_gap_variable_jurisdiction', nor does it mention any prerequisites or exclusions. The guidance is contextual but lacks explicit alternatives.

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