US Government Open Data MCP

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds context by explaining the tool's limitation ('BLS doesn't have a search API') and that it offers 'curated series IDs,' which helps the agent understand it's a predefined lookup rather than a dynamic search. However, it lacks details on output format, rate limits, or error handling, so it only partially compensates beyond annotations.

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 concise and front-loaded, starting with the core purpose. The second sentence provides necessary context, and the topic list is efficiently presented. However, the topic list could be integrated more smoothly, and there's minor redundancy with the schema, but overall it's well-structured with minimal waste.

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 simplicity (2 parameters, 100% schema coverage, read-only annotation) and no output schema, the description is adequate but not complete. It explains the tool's purpose and limitation but lacks details on what the output looks like (e.g., format of returned series IDs) or any prerequisites, leaving some gaps for the agent to infer.

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 'topic' (including enum-like values) and 'state' (two-letter code). The description lists the same topics, adding no new semantic information beyond the schema. Since the schema is comprehensive, the baseline score of 3 is appropriate, as the description does not enhance parameter understanding.

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: 'Look up popular BLS series IDs by topic.' It specifies the verb ('look up'), resource ('BLS series IDs'), and scope ('by topic'), and distinguishes itself by noting 'BLS doesn't have a search API, so this provides curated series IDs for common topics.' However, it does not explicitly differentiate from sibling tools like 'bls_series_data' or 'bls_cpi_breakdown', which slightly reduces clarity.

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 implies usage context by listing specific topics (e.g., 'employment', 'cpi') and mentioning it's for 'common topics' due to BLS lacking a search API. It does not explicitly state when to use this tool versus alternatives like 'bls_series_data' or provide exclusions, leaving some ambiguity for the agent.

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