Predict a person's age from their first name; add a country code to localize the estimate.
Predict the age of a person based on their first name.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | First name to analyze | |
| country_id | No | ISO 3166-1 alpha-2 country code for localization |
Changes observed during successful MCP inspections.
v0.1.11Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It doesn't disclose that this is a statistical estimate (not a fact), what confidence/accuracy to expect, rate limits, or response structure. 'Predict' hints at estimation but no behavioral detail is given.
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?
Single, front-loaded sentence with zero waste. Appropriate length for a simple 2-param tool.
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?
Adequate for a simple estimation tool, but with no annotations and no output schema, the description leaves the agent guessing about return format and the statistical nature of the prediction. Could note that results are estimates, not guarantees.
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 coverage is 100%, so both parameters (name, country_id) are documented in the schema. The description adds no parameter-level detail beyond what's already there. Baseline 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?
States a specific verb+resource: predict age of a person from first name. Clear enough to distinguish from genderize_name/nationalize_name siblings, though it doesn't explicitly say it's name-based demographic estimation.
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?
No guidance on when to use this vs alternatives like genderize_predict or nationalize_predict, which are clearly analogous name-analysis tools in the sibling set. No exclusions or prerequisites stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.