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dylancharris

ESPN Fantasy Basketball MCP Server

by dylancharris

should_i_bid

Get a recommendation on whether to bid for the player currently nominated, including a suggested bid amount and reasoning. Make confident waiver decisions in ESPN fantasy basketball.

Instructions

Get recommendation on whether to bid for the current player being nominated.

Args:
    current_player_id: ID of player currently being nominated
    team_id: Your team ID (optional, uses ESPN_TEAM_ID env var)
    league_id: ESPN Fantasy Basketball league ID (optional, uses ESPN_LEAGUE_ID env var)
    year: Season year (e.g., 2025) (optional, uses ESPN_YEAR env var or defaults to 2025)
    espn_s2: ESPN authentication cookie for private leagues (optional, uses ESPN_S2 env var)
    swid: ESPN SWID cookie for private leagues (optional, uses ESPN_SWID env var)

Returns:
    Dictionary with bid recommendation, suggested amount, and reasoning

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
swidNo
yearNo
espn_s2No
team_idNo
league_idNo
current_player_idYes
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 discloses env var fallbacks and the use of auth cookies for private leagues, but does not explicitly state read-only behavior, error conditions, or limitations. This is partially transparent but not fully comprehensive.

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 well-structured with a clear purpose line, an Args section, and a Returns section. Every line provides valuable information without redundancy, making it appropriately concise and front-loaded.

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?

The description adequately covers the tool's purpose, all arguments, and the return shape, which is sufficient given the tool's moderate complexity and lack of output schema. It could add examples or edge-case details but is otherwise complete.

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

Parameters5/5

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

The input schema has 0% description coverage, but the description compensates by explaining all six parameters, including defaults, env var fallbacks, and purpose. This adds significant meaning beyond the schema's bare type definitions.

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 purpose with a specific verb ('Get recommendation') and resource ('current player being nominated'). It distinguishes from sibling tools like who_should_i_target_next, which focuses on targeting rather than bidding.

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 usage during an auction nomination by referencing 'current player being nominated,' giving clear context. However, it does not explicitly mention when not to use it or compare with alternatives, leaving out exclusions.

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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