Returns every name that appeared in SSA records for the first time in the given year — genuine linguistic novelties, celebrity imports, invented spellings, or names newly crossing the 5-birth reporting threshold.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Birth year to find debut names for |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses the tool's inclusion criteria (including names crossing the 5-birth threshold, not just true novelties) and emphasizes it returns 'every' name, implying a complete list. It does not mention output format or pagination, but for a read-only query tool, 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 a single, front-loaded sentence with the core action first, followed by a clarifying list. While the list is useful for defining 'debut', it adds length; the text is not overly verbose but could be slightly tighter, earning a 4 rather than 5.
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 simple one-parameter tool with no annotations or output schema, the description provides enough context: it states what it returns, the data source (SSA records), and the precise meaning of 'debut'. It could be improved by mentioning the return format or edge cases (e.g., empty results), but it is sufficiently complete for an agent to select and invoke the 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?
The input schema already provides 100% coverage for the single parameter 'year' with a clear description. The tool description does not add additional semantics beyond restating 'given year', so the baseline of 3 is appropriate—the 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 returns names first appearing in SSA records for a given year, using a specific verb ('Returns') and a precise resource ('every name that appeared in SSA records for the first time'). It also explains the scope with categories (novelties, celebrity imports, invented spellings, threshold-crossing), which differentiates it from sibling tools like get_year_names or get_name_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 clear context on when to use the tool (for finding debut names in a specific year) and implies that it is the right choice for this focused query. However, it does not explicitly mention alternatives or exclusions, such as telling the agent to use get_year_names for all names or search_names for general search, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
