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sofascore_draft_picks

SofaScore league draft picks. Returns one round of a league draft: each pick with the overall and in-round number, the drafting team, and the drafted prospect (name, position, college or club, top-prospect flag and the player id when…

Instructions

SofaScore league draft picks. Returns one round of a league draft: each pick with the overall and in-round number, the drafting team, and the drafted prospect (name, position, college or club, top-prospect flag and the player id when SofaScore has one), plus the teams that hold no pick in that round. The league enum accepts nba (rounds 1 and 2) and nfl (rounds 1 to 7); other rounds return 400. Get year from the draft endpoint's draft.year and previous_draft.year; SofaScore keeps only recent drafts, so an older year returns 404. Returns 404 when SofaScore has no picks for that year and round.

Input Schema

NameRequiredDescriptionDefault
yearYesFour-digit draft year
roundYesDraft round: 1 to 2 for nba, 1 to 7 for nfl
leagueYesLeague whose draft to return

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.12

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that out-of-range rounds return 400, that old years and missing picks return 404, and that SofaScore keeps only recent drafts. It omits any mention of auth or rate limits, but the error and data-availability semantics are substantive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose and return shape, then error/sourcing details. Dense but each sentence adds operational information; slightly verbose with the full field enumeration, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must describe return values, which it does thoroughly (pick numbers, team, prospect fields, teams with no pick). Combined with the 400/404 semantics, an agent has enough to call it correctly and interpret errors.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and already documents the round ranges, but the description adds meaning by tying `league` values to round limits and, importantly, explaining where `year` comes from (the draft endpoint). That sourcing hint is value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Returns one round of a league draft') and enumerates the returned fields in enough detail to distinguish it from the sibling sofascore_draft. An agent knows exactly what payload to expect without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides concrete context: the league enum values with their valid round ranges, and directs the agent to source `year` from the draft endpoint's draft.year/previous_draft.year. It does not name explicit when-not-to-use alternatives, but the sourcing pointer and error conditions give clear operational guidance.

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

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