US Government Open Data MCP

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

Annotations provide readOnlyHint=true, which the description aligns with by describing a data retrieval operation ('Get'). The description adds valuable context beyond annotations: it specifies the data scope (1999–2016, by state/sex/race/age) and highlights its relevance for opioid crisis analysis. However, it doesn't mention potential limitations like data completeness or update frequency.

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 extremely concise—two sentences that efficiently convey purpose, scope, and relevance. Every word earns its place, with no redundant information. The structure is front-loaded with the core functionality followed by contextual importance.

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?

For a read-only tool with full schema coverage and no output schema, the description provides adequate context: purpose, data scope, and relevance. It could be more complete by mentioning output format or data granularity, but given the annotations and schema richness, it's sufficiently informative for agent 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%, with all parameters well-documented in the schema itself. The description does not add any parameter-specific details beyond what's in the schema (e.g., it doesn't clarify parameter interactions or default behaviors). This meets the baseline expectation when schema coverage is high.

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 ('Get drug poisoning/overdose mortality') and resources ('by state'), including temporal scope (1999–2016) and breakdown dimensions (state, sex, race, age group). It distinguishes from sibling tools like 'cdc_mortality_rates' by specifying the drug overdose focus, which is critical for opioid crisis analysis.

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 ('Critical for opioid crisis analysis') but does not explicitly state when to use this tool versus alternatives like 'cdc_causes_of_death' or 'cdc_mortality_rates'. No exclusions or prerequisites are mentioned, leaving the agent to infer appropriate usage scenarios.

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