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

With no annotations, the description carries the burden of disclosure. It transparently explains the scope (top 100 names of each sex) and the comparison nature (vs. prior year), and lists the output categories. However, it does not disclose edge-case behavior (e.g., what happens for the earliest year with no prior data), nor does it detail the output structure or whether it includes rank values. It is adequate but not rich.

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, information-dense sentence, front-loaded with the core concept and followed by a clear list of output categories. Every word earns its place; there is no fluff.

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 tool with one parameter, no output schema, and no annotations, the description provides a solid understanding of what is returned (gainers, losers, new entrants) and the scope (top 100 per sex). It does not mention whether results are ranked or how the two sexes are presented, but these are minor gaps for an agent to choose and invoke the tool effectively.

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%: the only parameter 'year' is described as 'Birth year to compare against the prior year.' The tool description echoes this by saying 'vs. the prior year,' adding no new semantic information beyond the schema. Baseline 3 applies.

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 what the tool does: it provides year-over-year rank changes for the top 100 names of each sex, including biggest gainers, losers, and new entrants. This is specific and distinguishes it from siblings like get_year_names (which likely lists names for a year) and compare_names (which likely compares specific names).

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: if the user needs year-over-year rank movements for the top names, this is the tool. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Usage context is clear but not directly stated.

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