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 states 'Bulk fetch' but doesn't clarify what 'bulk' entails (e.g., pagination, rate limits, data format, or whether it's a read-only operation). The description lacks details on authentication needs, error handling, or any side effects, leaving significant gaps for a tool that presumably retrieves large datasets.

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 brief and front-loaded with the core purpose ('Bulk fetch a FRED release.'). The second sentence provides useful examples without unnecessary elaboration. However, it could be more structured by explicitly separating purpose from examples or adding bullet points for clarity.

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 of a bulk data fetch tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., data format, structure, or fields), how to handle large datasets, or any performance considerations. For a tool likely dealing with substantial economic data, more context is needed to ensure proper usage.

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 both parameters ('release_id' and 'limit') with descriptions. The description adds minimal value by providing examples of common release IDs (e.g., 53 for GDP), but doesn't explain parameter interactions, default behaviors, or constraints beyond what's in the schema. This meets the baseline for high schema coverage.

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: 'Bulk fetch a FRED release.' It specifies the verb ('fetch') and resource ('FRED release'), and the examples (GDP, Employment, CPI, Rates) help clarify the type of data. However, it doesn't explicitly differentiate from sibling tools like 'fred_series_data' or 'fred_search', which might offer alternative ways to access FRED 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 no guidance on when to use this tool versus alternatives. It mentions common release IDs (e.g., 53 for GDP), but doesn't explain when to choose this bulk fetch over other FRED tools (e.g., 'fred_series_data' for specific series or 'fred_search' for discovery). There's no mention of prerequisites, limitations, or typical use cases.

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