Side-by-side comparison of 2-3 names: full yearly series for each so trends can be plotted or contrasted directly.
| Name | Required | Description | Default |
|---|---|---|---|
| names | Yes | Names to compare, e.g. ["Michael", "James", "David"] |
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 of behavioral disclosure. It states that the output is full yearly series for each name, which implies a read-only operation, but it does not describe the output format, year range, or behavior for names with no data. This basic transparency is adequate but lacks depth.
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 that immediately states the purpose, then elaborates on the benefit. Every word earns its place; there is no fluff or repetition of schema details.
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?
The tool is simple (one parameter, no annotations, no output schema), and the description adequately explains the core behavior and intended use case. It mentions the output (full yearly series) and the purpose (plotting/contrasting). However, it does not detail the exact return structure, which would be expected without an output schema, so a slight deduction is made.
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 schema already provides a clear description of the 'names' parameter, including min/max items and an example. The description adds context about the output (full yearly series) but does not add new meaning to the parameter itself. Since schema coverage is 100%, the baseline score of 3 is appropriate.
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 function: side-by-side comparison of 2-3 names, with full yearly series for each. This distinguishes it from siblings like get_name_data (which likely handles a single name) and other name-specific tools. The verb 'comparison' and resource 'names' are explicit.
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 when to use the tool: when you need to compare 2-3 names and plot or contrast their trends. It does not explicitly name alternatives or give exclusion criteria, but the context is clear and distinct from sibling tools that handle single names or different groupings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
