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

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the description is free to add the behavior that matters: a concrete credit cost ('Costs 5 credits') and per-source data availability limits (earnings empty for DPWT and LIV; no Race to Dubai or CME Globe points; tournament stat lines only for PGA Tour from 2011). These are exactly the caveats an agent cannot get from structured fields and would otherwise produce silently wrong answers.

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 usage directive is front-loaded and the dense stat enumeration is grouped logically by data source rather than dumped as a flat list. It is long, but nearly every clause (glosses, league restrictions, credit cost) earns its place; a bulleted structure would read faster than the single run-on enumeration.

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, the description needn't explain return values, and it correctly spends its budget elsewhere: stat semantics, league/stat compatibility, credit cost, and sample-size context ('with each player's sample'). Combined with 100% schema coverage and full annotations, nothing needed to call this correctly is missing.

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 already 100%, so the baseline would be 3, but the description goes further and glosses the entire stat enum semantically — sg_par3/4/5 are defined as strokes versus field on those hole types, field-strength adjusted, and each stat is grouped by source (rounds/holes, results, tournament stat lines). That is real meaning the schema's bare 'The stat to rank' does not convey, and it is the parameter most likely to be mis-selected.

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 opening clause states a specific verb-style trigger and resource: 'a season's leaders in one stat, with each player's sample.' That scope (season-level, single-stat ranking) implicitly separates it from get_leaderboard and get_player_stats, but no sibling is named explicitly, so the differentiation is inferred rather than stated.

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?

'Use for a season's leaders in one stat' is an explicit usage trigger, and the stat glossary adds conditional guidance (sg_* is 'PGA Tour and Korn Ferry Tour only, score-based, not shot data'; cup_points is 'PGA Tour only'). It stops short of naming when to prefer a sibling such as get_leaderboard or get_player_stats, so it lacks explicit exclusions.

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