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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety and determinism profile is covered. The description adds one genuinely useful behavioral fact beyond that: results are aggregated by position and include counts plus physical averages, i.e. pre-computed summary data rather than individual records. It says nothing about grouping granularity, filter interaction, or result size.

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?

A single short sentence with the aggregation scope front-loaded and no filler. It is efficient, though the extreme brevity means it omits information that would actually help an agent call it correctly.

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?

An output schema exists, so return values need not be explained. However, for a tool with two undocumented filter parameters and a closely named sibling, the description omits filtering behavior, aggregation granularity, and any routing guidance, leaving notable gaps an agent must fill by trial.

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 0% for two optional parameters (conference, subdivision), so the description carries the full burden — yet it never mentions that results can be scoped by conference or subdivision, nor what values those accept. An agent cannot tell from the text that these filters narrow the aggregation rather than being ignored.

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 uses a specific verb ('Get') with a specific resource ('football player counts and physical averages by position'), so an agent knows this returns aggregated position-level metrics rather than raw player or team data. It does not explicitly distinguish itself from the similarly named sibling 'get_position_stats' or from 'get_football_stats', leaving the football-specific vs. general split to inference.

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?

There is no when-to-use guidance, no exclusions, and no mention of alternatives such as 'get_position_stats' or 'get_football_stats'. The agent must guess whether this is the right tool when it wants per-position aggregates versus player-level or team-level stats.

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