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asd-git-master

AltSportsLeagues MCP Server

score_partnership

Evaluates a league's partnership potential by analyzing data quality, market demand, sportsbook interest, integration complexity, and revenue potential, returning a score with recommendations.

Instructions

Score a potential partnership opportunity with a league.

Evaluates how well a league fits as a partnership candidate based on data quality, market demand, sportsbook interest, integration complexity, and revenue potential. Returns a multi-factor partnership score with recommendations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
league_idYesUUID of the league to score.
parametersNoOptional dict of partnership-specific parameters or weights.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions that the tool returns a score with recommendations, but does not discuss permissions, side effects, rate limits, or any other behavioral traits. This is insufficient for an agent to fully understand the tool's behavior.

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 extremely concise, with two short paragraphs that front-load the purpose. Every sentence adds value, and there is no redundancy or unnecessary detail.

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?

Given the presence of an output schema (which should document return values), the description sufficiently covers inputs, evaluation factors, and output nature. It could include more detail on scoring range or recommendation format, but it is largely complete for the tool's purpose.

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 coverage is 100%, providing basic descriptions for parameters. The description adds value by explaining the factors considered (data quality, market demand, etc.) and the nature of the output (multi-factor score with recommendations), which go beyond the schema's simple parameter descriptions.

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: to score a partnership opportunity with a league, evaluating multiple factors and returning a score with recommendations. It distinguishes from siblings by focusing specifically on partnership scoring, which is unique among the listed sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. Given the many sibling tools, this lack of usage context is a significant gap.

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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