US Government Open Data MCP

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

With no annotations provided, the description carries the full burden. It discloses useful behavioral traits: data is refreshed daily, and it supports multiple search methods. However, it lacks details on rate limits, authentication needs, error handling, or pagination behavior beyond what's in the schema, leaving gaps for a tool with 16 parameters.

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 core purpose, followed by search methods and use cases, all in three efficient sentences. Every sentence adds value without redundancy, making it appropriately sized and well-structured.

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 (16 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers purpose and usage well but lacks behavioral details like response format, error cases, or performance constraints. For a search tool with many parameters, more context would enhance 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?

Schema description coverage is 100%, so the schema already documents all 16 parameters thoroughly. The description adds minimal value beyond the schema by mentioning search types (keyword, exact field match, filters) but does not provide additional syntax or format details. Baseline 3 is appropriate when 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 with specific verbs ('search', 'find') and resources ('GSA CALC+ ceiling rates', 'federal labor categories', 'GSA MAS professional services contracts'). It distinguishes itself from sibling tools by focusing on federal labor rates rather than other datasets like BEA, BLS, or census data.

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 clear context for when to use the tool ('market research, IGCEs, and competitive pricing') and mentions search methods (keyword, exact field match, browse with filters). However, it does not explicitly state when not to use it or name specific alternatives among siblings, though the context implies it's for federal labor rates specifically.

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