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

Annotations already mark this as read-only. The description adds meaningful context beyond that: a credit cost ('Costs 5 credits'), source-specific availability years (2016+ vs 2018+), and the kinds of data each source provides. This helps the agent anticipate side effects and data scope without contradicting annotations.

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?

Four sentences, each earning its place: use case, NGS metrics, PFR metrics, and usage/cost. The purpose is front-loaded, and the metric lists are compact and informative without 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?

With an output schema present, return-value details are already covered. The description supplies the missing operational context: credit cost, source-year ranges, filter workflow, and metric examples. Nothing an agent needs to invoke this correctly is left out.

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 baseline is 3. The description adds value by associating metric families with specific source enum values (e.g., time to throw for NGS, pressures for PFR), which clarifies what each source actually returns. It also reinforces filter dimensions (season, week, player, team) already present in the schema.

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 ('tracking and charting') and resource ('metrics the box score does not carry'), then enumerates concrete metric examples for each source (NGS and PFR). This clearly distinguishes it from box-score stat tools like get_player_stats and get_team_stats.

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?

It states an explicit use case ('metrics the box score does not carry') and gives a usage pattern ('Pick a source, then filter by season, week, player or team'). However, it does not name a specific alternative tool for box-score stats, so the exclusion is implied rather than explicit.

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