get_league_table

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

With no annotations provided, the description carries full burden. It discloses that results are sorted by 'attacking strength (xG per 90 minutes)', which is useful behavioral context beyond basic retrieval. However, it lacks details on rate limits, authentication needs, pagination, error conditions, or whether this is a read-only operation (implied by 'Get' but not explicit). The description doesn't contradict annotations (none exist).

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 perfectly structured and concise: purpose statement first, behavioral detail second, parameter documentation third. Every sentence earns its place - no redundant information. The three-sentence format is front-loaded with the core functionality.

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?

Given 1 parameter with 0% schema coverage, no annotations, but an output schema exists, the description does well. It explains the parameter semantics and sorting behavior. The output schema existence means return values don't need description. However, for a data retrieval tool, additional context about data freshness, source, or limitations would enhance completeness.

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%, so the description must compensate. It provides meaningful semantics for the single parameter: 'league: League slug, name, or ID (default: EPL)' - explaining what the parameter represents and acceptable formats. This adds substantial value beyond the bare schema. However, it doesn't provide examples of valid slugs/names/IDs beyond the default 'EPL'.

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 the tool's purpose: 'Get all teams in a league with their xG statistics' - a specific verb ('Get') and resource ('teams in a league with xG statistics'). It distinguishes from sibling tools (list_leagues, predict_match) by focusing on team statistics rather than league listing or match prediction. However, it doesn't explicitly contrast with siblings beyond this implicit differentiation.

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 context through 'Returns teams sorted by attacking strength' and the league parameter, suggesting this is for analyzing team performance metrics. However, it provides no explicit guidance on when to use this tool versus alternatives like predict_match for match outcomes or list_leagues for league metadata. No when-not-to-use scenarios or prerequisites are mentioned.

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