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bealmot

sleeper-mcp

by bealmot

matchup_odds

Calculate win probability for each head-to-head fantasy football matchup in a given week, accounting for weekly scoring variance.

Instructions

Win probability for every head-to-head matchup in a week.

Treats both team scores as normal around their estimated strength, so the answer accounts for how noisy a fantasy week is: a 15-point edge is much less decisive than it sounds when weekly swings are 25 points.

Args: week: which week. Defaults to the current one. league_id_: override the configured league.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weekNo
league_id_No

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations, so description must carry the full behavioral burden. It explains the statistical model (normal distribution around estimated strength, noise adjustment) which is useful, but does not explicitly state read-only nature, authentication requirements, or league configuration assumptions.

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?

Front-loaded purpose, followed by a concise model explanation, then an Args list. Every sentence adds value; no redundancy.

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?

Output schema exists, so return values need not be explained. The description covers purpose, model, and parameters. Missing explicit safety profile (e.g., read-only) and prerequisites, but adequate for a probabilistic odds tool.

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 description coverage is 0%, so the description must explain parameters. It does so for both: week (which week, defaults to current) and league_id_ (overrides configured league). Clear semantics, though no format details beyond schema types.

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?

States a specific resource and computed metric: win probability for every head-to-head matchup in a week. Clear what the tool does, but does not explicitly distinguish it from sibling tools like matchup or playoff_odds.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives such as matchup or playoff_odds. Usage is only implied by the purpose statement.

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