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LuccaBessa

sleeper-mcp

by LuccaBessa

Get Matchups

get_matchups

Get all matchups for a Sleeper league in a specified week, with each matchup listing the two opposing teams and player names.

Instructions

Get all matchups in a league for a given week. Teams sharing a matchup_id face each other. Player IDs are annotated with names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weekYesThe week to fetch matchups for (e.g. 1).
league_idYesThe Sleeper league ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that teams sharing a matchup_id face each other and that player IDs are annotated with names, which is useful behavioral context. However, it doesn't mention whether this is a read-only operation, any rate limits, or what happens if no matchups exist for the week. The description adds some value but not comprehensive behavioral disclosure.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the core function, and adds a clarifying detail about matchup_id and player ID annotations. Every sentence earns its place; no wasted words.

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 read-style tool with two fully documented parameters, the description is largely complete. It explains the grouping logic and the player ID annotation, which are the non-obvious aspects. It could mention the return format or edge cases (e.g., empty weeks), but given the simplicity and full schema coverage, the gaps are minor.

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?

Schema description coverage is 100%, so the schema already documents both parameters (league_id and week) with descriptions. The description adds the context that week is used to filter matchups, but doesn't add new parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate.

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?

The description clearly states the tool's function: retrieving all matchups in a league for a given week. It specifies the resource (matchups), the scope (league), and the key parameter (week). It also adds a useful detail about matchup_id grouping and player ID annotations, which helps distinguish it from other league-related tools.

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?

The description implies when to use this tool: when you need matchups for a specific league and week. It doesn't explicitly name alternatives or exclusions, but the sibling list shows other tools like get_league, get_rosters, get_transactions, which are clearly different. The context is clear enough for an agent to select it appropriately.

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