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Ball Ranks

Get season rankings

get_season_rankings
Read-onlyIdempotent

Return a paginated Ball Ranks season ranking board for fantasy basketball or football. Basketball uses nine-category per-game rankings; football accepts standard, half-PPR, or PPR scoring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
modelNov0
sportYes
offsetNo
seasonNo
scoring_formatNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaYes
queryYes
totalYes
rankingsYes
sourceUrlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world, non-destructive behavior, so the safety profile is covered. The description adds real domain context beyond that: basketball returns nine-category per-game ranks while football is driven by standard/half-PPR/PPR scoring, which tells the agent how the result set will differ by sport.

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 tightly written sentences with no filler, front-loading the core purpose before the sport-specific qualifiers. Nothing is redundant with the schema and no sentence 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?

Output schema exists, so return values need no explanation, and the annotations cover safety. The description covers sport-specific semantics and pagination at a high level, but leaves the opaque 'season' format and the 'model' version parameter unexplained, which is a real gap for a six-parameter tool.

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

Parameters2/5

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

Schema description coverage is 0% across six parameters, so the description carries the full burden and largely fails. It clarifies that scoring_format applies only to football and what basketball rankings mean, but says nothing about 'model' (v0/v1), 'season' (accepts int or string up to a huge bound), 'limit', or 'offset' beyond the word 'paginated'.

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 gives a specific verb and resource ('Return a paginated Ball Ranks season ranking board') and specifies the sport-dependent ranking semantics. It implicitly separates itself from get_week_rankings by scoping to a season, but never names a sibling explicitly, so differentiation is left to inference.

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?

Usage is implied by the word 'season' (as opposed to week or player rankings) but the description never states when to choose this tool over get_player_rankings or get_week_rankings, nor any exclusions or prerequisites. An agent must infer the routing decision from the tool name alone.

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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