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LitVM TCG Oracle

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 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. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden, and it does meaningful work: it discloses merkle-commit timing ('BEFORE games score'), the on-chain registry/stream involved, and what each invocation mode returns. It stops short of 5 because it omits details like auth requirements, error behavior, or rate limits, though none are clearly critical for a read-style lookup.

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?

Three dense sentences, each earning its place: the first establishes what the league is, the second explains the merkle-commit transparency trait, and the third maps parameter variants to outputs. There is no redundant padding or repetition of the tool name.

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 single-optional-parameter tool with an output schema present, the description covers the key operative questions: what the tool is about, what the parameter means, and what each call variant returns. The only slight gap is that 'No token_id' vs the schema's default of 0 is not stated as an explicit equivalence, leaving a small edge-case ambiguity.

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 only defines token_id as an integer with default 0 and 0% schema description coverage. The description fully compensates by explaining exactly what the parameter controls: omitting it yields the league feed with standings and commit txs, while providing it yields a specific soul's lineup, traits, and strategy.

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 identifies the resource ('The Undesirables fantasy league on LitecoinVM') and the retrieval behavior, splitting between a league feed and a token-specific soul lineup. The fantasy-league vocabulary is distinct enough that an agent can tell this from the loan, market, sports, and oracle sibling tools without opening schemas.

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?

The description gives clear conditional guidance for the token_id parameter ('No token_id' vs 'With token_id'), which is useful for invocation. However, it never explicitly says when to prefer this tool over a sibling alternative or lists exclusions, so cross-tool selection guidance is only implied by domain.

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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