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lacausecrypto

Sports Hub MCP Server

by lacausecrypto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

squiggle: Get ladder

squiggle_get_ladder
Read-onlyIdempotent

Get the projected AFL ladder for a given year and round by prediction model, including projected wins and mean rank.

Instructions

Get the projected AFL ladder for a given year and round, by prediction model. Each model gives its own projected wins / mean rank.

Input Schema

NameRequiredDescriptionDefault
yearYesSeason year
roundYesRound number
fieldsNoKeys to keep (comma-separated).
sourceNoModel source id (use squiggle_get_sources)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.4.1
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • addedInput schema / properties / fields
      Added value: +{
+  "description": "Keys to keep (comma-separated).",
+  "type": "string"
+}
    • removedInput schema / properties / round / maximum
      Removed value: -9007199254740991
    • removedInput schema / properties / source / maximum
      Removed value: -9007199254740991
  2. Changed3 schema fields changedv1.3.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / round / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / source / maximum
      Added value: +9007199254740991
  3. First observedv1.2.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint), so the bar is lower. The description adds real behavioral value by explaining the output shape — 'each model gives its own projected wins / mean rank' — which tells the agent this produces per-model projections rather than a single ladder.

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?

Two sentences with zero waste: the core purpose is front-loaded and the follow-up sentence adds only the output semantics. Nothing redundant or padding.

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 read-only query tool with full annotation coverage and 100% schema coverage, little is missing. The description even characterizes the return values, which compensates for the absent output schema.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents year, round, fields and source, including the hint to use squiggle_get_sources. The description adds no syntax or default details beyond what the schema provides, so baseline 3 is appropriate.

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?

Names a specific verb+resource and scope: 'Get the projected AFL ladder for a given year and round, by prediction model.' The word 'projected' implicitly separates it from squiggle_get_standings, but the description never names that sibling to make the distinction explicit.

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?

States the context (a given year and round) and that output is model-based, which implies usage. However it gives no when-not guidance and never points to the closely related squiggle_get_standings or squiggle_get_tips so the agent can choose between them.

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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