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DanielTomaro13

sportsdata-mcp

sleeper_user_leagues

Read-onlyIdempotent

Retrieve all leagues a user participates in for a given sport and season, returning league IDs and details to locate a specific league.

Instructions

Every league a user is in for one sport and season — how you get a league_id from a username.

Returns: [{league_id, name, season, status, sport, total_rosters, scoring_settings, roster_positions, settings, draft_id, previous_league_id}] (top-level array)

Example: A user's 2025 NFL leagues {"user_id": "483459259485384704", "sport": "nfl", "season": "2025"}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportNoSport.nfl
seasonYesSeason year, e.g. '2025'. Required — part of the URL path.
user_idYesNumeric user_id from sleeper_user (NOT the username). Required — part of the URL path.
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and openWorld hints. The description adds 'Auth: none needed' and explicitly shows the return array fields, contributing useful behavioral context 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.

Conciseness4/5

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

The description is compact and well-structured, including a returns list and a concrete example. The only minor waste is the misleading 'from a username' phrasing.

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?

For a simple list tool without an output schema, the description covers the key return fields, auth, and an example. It is complete enough to invoke correctly, though it could clarify the source of user_id.

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

Parameters3/5

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

Input schema has 100% coverage with useful descriptions, so the baseline is 3. The description's example demonstrates realistic values but doesn't add deeper parameter semantics beyond the schema.

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

Purpose4/5

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

Clearly states it lists all leagues for a user filtered by sport and season, with the specific use case of deriving a league_id. However, the phrase 'from a username' contradicts the actual parameter which requires a numeric user_id, per the schema.

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

Usage Guidelines3/5

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

Provides a clear implied use case: 'how you get a league_id from a user.' It does not explicitly mention alternatives like sleeper_league or sleeper_user, nor any exclusions, so the guidance is sufficient but not fully explicit.

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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