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 describes a search operation but lacks details on behavioral traits such as pagination behavior (implied by 'page' and 'per_page' parameters but not explained), rate limits, authentication needs, or what the response format looks like (no output schema). For a search tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that front-loads the core functionality ('Search for federal election candidates') and lists key parameters concisely. It avoids redundancy and wastes no words, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's purpose.

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 (7 parameters, no annotations, no output schema), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context (e.g., pagination, response format) and usage guidelines. The schema provides full parameter documentation, but without annotations or output schema, the description should do more to compensate, especially for a search tool where result handling is critical.

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 description lists search dimensions (name, state, party, office, election year), which aligns with the input schema parameters. However, schema description coverage is 100%, meaning the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by summarizing the searchable fields but does not provide additional syntax, format, or usage details. Baseline 3 is appropriate when 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: 'Search for federal election candidates by name, state, party, office, or election year.' It specifies the verb ('Search'), resource ('federal election candidates'), and key search dimensions. However, it does not explicitly differentiate from sibling tools like 'fec_search_committees' or 'fec_top_candidates', which are related but target different resources, leaving some ambiguity in sibling context.

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 no guidance on when to use this tool versus alternatives. It mentions the data source (FEC) but does not indicate when to choose this over other FEC tools (e.g., 'fec_search_committees' for committees) or other candidate-related tools. There are no explicit when/when-not instructions or named alternatives, leaving usage context implied at best.

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