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 full burden. It mentions the tool is 'useful for identifying trends,' which hints at read-only behavior but does not explicitly state it's a query (not a mutation), disclose rate limits, authentication needs, or error handling. For a tool with 7 parameters and no annotations, this leaves significant behavioral gaps.

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 two concise sentences with zero waste: the first states the core functionality, and the second provides usage context. It is front-loaded and efficiently communicates essential information without redundancy.

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 moderate complexity (7 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and hints at usage but lacks details on behavioral traits, output format, or sibling tool differentiation. With no annotations or output schema, more completeness would be beneficial.

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 fully documents all 7 parameters. The description adds no parameter-specific details beyond implying time-based aggregation via 'by time period,' which is already clear from the schema's 'group' parameter. Baseline 3 is appropriate as the schema does the heavy lifting.

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 federal spending aggregated by time period (monthly, quarterly, or fiscal year).' It specifies the verb ('Get'), resource ('federal spending'), and aggregation method, but does not explicitly differentiate from sibling tools like usa_spending_by_agency or usa_spending_by_state, which focus on different aggregation dimensions.

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 implied usage context with 'Useful for identifying trends,' suggesting this tool is for trend analysis over time. However, it lacks explicit guidance on when to use this versus other usa_spending_* tools (e.g., by agency or state) or any prerequisites/exclusions, leaving the agent to infer from parameter names.

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