US Government Open Data MCP

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

The description adds behavioral context beyond annotations: it specifies the tool is for 'Autocomplete/suggest' functionality, which implies it returns partial matches based on input text. Annotations already declare readOnlyHint=true, so the agent knows it's safe. The description doesn't mention rate limits, pagination, or error behavior, but with annotations covering safety, this is adequate.

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 sentence states the purpose, and the second provides usage guidelines. It's front-loaded and efficiently 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 tool's low complexity (2 parameters, read-only, no output schema), the description is complete enough. It covers purpose, usage, and context. However, it doesn't detail the return format (e.g., list of strings) or potential limitations, which could be helpful but isn't critical for this simple tool.

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%, with clear descriptions for both parameters ('text' and 'size'). The description mentions 'Partial company name to search' which aligns with the schema but doesn't add significant semantic value beyond it. 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 with a specific verb ('Autocomplete/suggest') and resource ('company names from the CFPB complaint database'). It distinguishes from sibling tools like 'cfpb_search_complaints' by specifying this is for finding exact company names before searching complaints, not for the actual complaint search.

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 explicitly states when to use this tool: 'Useful for finding the exact company name before searching complaints.' This provides clear context for usage (as a precursor to complaint searches) and implies an alternative (using 'cfpb_search_complaints' after obtaining the exact name).

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