Skip to main content
Glama
Tarune28

ESPN Fantasy Football MCP Server

by Tarune28

get_team_analysis

Analyze a fantasy football team for trade and improvement advice: get roster trends, bye-week conflicts, position strength vs league average, and bench depth.

Instructions

Aggregated snapshot of a team for trade / improvement advice.

Args: team_name: Team name or owner name (fuzzy).

Returns:

  • Full roster with average points and a last-3-weeks trend (up/down/flat)

  • Bye-week conflicts (weeks where multiple starters are out)

  • Position-group strength vs the league average at that position

  • Bench depth by position

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
team_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the concrete analysis dimensions returned (trend, bye weeks, positional strength, bench depth) and implies a read-only aggregate, but says nothing about permissions, refresh/caching behavior, or whether the snapshot is computed live.

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 one-line purpose followed by tightly scoped Args and Returns sections; every bullet adds information. Slightly list-heavy, 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?

An output schema exists, so return values did not need restating, yet the description's summary of them helps an agent decide relevance. For a single-param read tool, the definition is essentially complete; only the absence of any usage routing against 19 siblings leaves a small gap.

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 0% for the single parameter, so the description must compensate, and it does: 'Team name or owner name (fuzzy)' tells the agent that owner names are accepted and matching is fuzzy. That is genuine semantic value beyond the bare 'team_name: string' 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?

The description states a specific resource and scope: 'Aggregated snapshot of a team for trade / improvement advice,' and enumerates the analytical outputs (trend, bye-week conflicts, positional strength, bench depth). This distinguishes it conceptually from raw-roster siblings like get_team_roster, though it never names an alternative explicitly.

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?

It gives a purpose context ('for trade / improvement advice') that implies when to reach for it, but offers no explicit when-to-use vs when-not guidance and does not point to siblings like get_trade_candidates or compare_teams. Usage is implied rather than stated.

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