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asd-git-master

AltSportsLeagues MCP Server

get_league_momentum

Identify which alternative sports leagues are trending up or down. Returns top gainers and decliners with valuation scores and momentum classifications.

Instructions

Retrieve the top movers and decliners across all leagues.

Returns leagues ranked by recent score change -- the biggest gainers and biggest losers. Each entry includes the league name, sport archetype, current valuation score, score change, growth trajectory, and momentum classification (rapid_expansion, strong_growth, steady, declining).

Use this to find which leagues are trending up or down right now. No parameters required -- returns the current market-wide movers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It implies read-only behavior and current data but does not detail data freshness, caching, or any potential side effects. Some additional context would be beneficial.

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?

Four concise sentences without redundancy. The description is efficiently structured: main action, return details, and usage guidance. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no nested objects) and the existence of an output schema, the description fully covers what the agent needs to know. It specifies output fields and purpose, making it complete.

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?

The input schema has no parameters, so the description adds value by explaining the output structure and fields. This meets the baseline expectation for zero-parameter tools and provides meaningful context beyond the schema.

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 'Retrieve the top movers and decliners across all leagues,' specifying a concrete verb and resource. It differentiates from sibling tools by focusing on momentum and includes details about the returned fields, making the purpose unambiguous.

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

Usage Guidelines4/5

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

The description advises 'Use this to find which leagues are trending up or down right now,' providing clear usage context. However, it does not explicitly mention when not to use this tool or contrast with siblings like compare_league_trajectories, which would improve guidance.

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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