games_get_league_draftFetch draft rounds, team selections, and pick results by sport, league, and optional year to review historical or current league drafts.
Fetch league draft rounds, team selections, and pick results for a draft year (e.g. the first overall pick).
| Name | Required | Description | Default |
|---|---|---|---|
| sport | Yes | e.g. basketball | |
| league | Yes | e.g. nba, eng.1 | |
| season | No | Draft year (the year it's held). Omit for ESPN's current. |
Changes observed during successful MCP inspections.
v2.0.0Input schema / properties / league / descriptionAdded value: +"e.g. nba, eng.1"Input schema / properties / season / descriptionAdded value: +"Draft year (the year it's held). Omit for ESPN's current."Input schema / properties / sport / descriptionAdded value: +"e.g. basketball"v1.2.9Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is fully covered. The description adds the useful detail of what data comes back (rounds, selections, pick results), but says nothing about response shape, pagination, or behavior when the draft year is absent.
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 front-loaded sentence with the verb and resource first and a parenthetical example at the end. There is no filler or redundancy.
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 read-only lookup with complete schema coverage, no output schema, and clear annotations, the description covers the essential content of the return. It is only minimally thin on the draft-year edge cases (e.g. invalid/absent year), which the schema partly handles.
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 100%, so sport, league, and season are already documented in the schema, including the note to omit season for ESPN's current data. The description's mention of a 'draft year' loosely mirrors the season parameter but adds no format or semantic detail beyond 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 gives a specific verb (fetch) and a precise resource (league draft rounds, team selections, pick results for a draft year), and the concrete example ('the first overall pick') sharpens the mental model. No other sibling tool covers drafts, so the resource itself differentiates it, though the description never explicitly contrasts with siblings.
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 what the tool returns but never says when to reach for it versus alternatives (e.g. games_get_league_events or games_get_transactions for related league data), nor any prerequisite or exclusion. Usage is only inferable from the resource name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.