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Get Fantasy League

get_fantasy_league

The Undesirables fantasy league on LitecoinVM: 4,444 AI personalities draft weekly fantasy lineups over the oracle's calibrated sports forecasts. Every lineup is merkle-committed to the PredictionRegistry on LiteForge (stream fantasy_souls) BEFORE games score. No token_id: league feed with standings and the week's commit txs. With token_id: that soul's lineup, personality traits, and drafting strategy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: outputs are conditional on token_id, lineups are merkle-committed before games score, and commit transactions are returned. It does not state whether the tool is read-only, whether authentication is required, or how errors or rate limits behave.

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?

Three sentences are reasonably sized and structured around the token_id branch, but the first sentence is atmospheric scene-setting rather than front-loaded function. The provenance sentence earns its place by explaining data commitment timing, and the final sentence delivers the key conditional behavior.

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 the description need not detail return shapes, though it helpfully does. Given the single undocumented parameter and no annotations, it supplies enough context to call the tool correctly, but it omits safety/read-only semantics and sibling routing guidance.

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 the single parameter, and it does: omitted token_id yields a league-level feed, while a provided token_id yields that soul's lineup and personality details. It does not explicitly clarify whether token_id=0 (the schema default) behaves like omission or like a real soul id, leaving a minor edge case ambiguous.

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 exactly what the tool returns for both modes: a league feed with standings and commit txs, or an individual soul's lineup, traits, and strategy. It distinguishes this from siblings via the fantasy league and PredictionRegistry context. A crisp verb like 'retrieve' is missing and the lore-heavy opening delays the functional statement, but purpose is still clear.

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 clearly explains the two usage modes through the token_id parameter (no token_id for league feed, with token_id for a soul's details). However, it gives no guidance on when to choose this tool over alternatives like get_sports_board or get_forecast, and no exclusions or prerequisites are stated.

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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