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. It discloses important behavioral traits: it mentions performance considerations ('Use preview_only=true first to check bill size before loading'), data size ranges ('Bills range from 5k chars to 500k+'), default limits ('Default limit is 100k chars'), and versioning details ('Version suffixes: enr, eh, es, ih, is'). However, it doesn't cover potential errors, authentication needs, or rate limits.

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 well-structured and appropriately sized. It front-loads the core purpose, follows with important usage guidelines, and ends with technical details. Every sentence adds value, though it could be slightly more concise by integrating some details (e.g., version suffixes) more tightly.

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 complexity (6 parameters, no annotations, no output schema), the description does a good job of covering key aspects: purpose, usage guidelines, behavioral traits, and parameter context. It lacks details on output format or error handling, but for a tool focused on retrieving text, the guidance on size and preview functionality compensates well.

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 baseline is 3. The description adds meaningful context beyond the schema: it explains the purpose of 'preview_only' ('to check bill size before loading'), provides practical advice on 'max_length' ('Most bills fit within 100k. Set higher for large omnibus bills'), and clarifies 'version' suffixes with their meanings. This enhances understanding of parameter usage.

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 explicitly states the tool's purpose: 'Get the FULL legislative text of a bill from GovInfo — the actual law language with section numbers, dollar amounts, legal citations, and provisions.' It uses a specific verb ('Get') and resource ('legislative text of a bill'), and distinguishes itself from sibling tools by specifying the exact content it provides (e.g., 'actual law language' vs. summaries).

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 explicit guidance on when to use this tool versus alternatives: 'Try congress_bill_summaries first for a quick CRS summary (~500-2000 chars). Only use this tool when the user needs exact legislative language, specific provisions, or dollar amounts from the bill text.' It clearly defines the use case and names a specific alternative tool.

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