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asd-git-master

AltSportsLeagues MCP Server

evaluate_league

Assess a league's overall value by scoring market potential, data quality, betting readiness, fan engagement, operational maturity, and risk deductions to generate a 0-1000 composite score and ASD Certificate Tier.

Instructions

Evaluate a league's value across multiple dimensions and assign a tier.

Runs the full valuation model: Market Potential (25%), Data Quality (20%), Betting Readiness (20%), Fan Engagement (15%), Operational Maturity (10%), and Risk Deductions (10%). Produces a 0-1000 composite score and an ASD Certificate Tier (1.1 through 4.9).

Optionally pass custom criteria weights or overrides.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
league_idYesUUID of the league to evaluate.
criteriaNoOptional dict of custom evaluation criteria or weight overrides.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so description carries full burden. Discloses that it runs a full valuation model with weighted components and allows custom criteria overrides. Doesn't mention side effects, but given 'evaluate' likely read-only, this is sufficient.

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 clear paragraphs: first sentence states main purpose, second details model components and output, third mentions optional override. No wasted words, front-loaded with key information.

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?

Output schema exists, covering return values. Description fully explains the valuation model, scoring dimensions, and output format (score and tier). Complete for a complex evaluation tool.

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?

Input schema has 100% coverage, so baseline 3. Description adds meaning for 'criteria' by specifying it can be custom evaluation criteria or weight overrides, which adds value 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?

Description states 'Evaluate a league's value across multiple dimensions and assign a tier' with specific verb and resource. Distinguishes from sibling 'assess_league_readiness' by focusing on comprehensive valuation rather than just readiness.

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?

Implies usage through description of what it does, but does not explicitly state when to use this over alternatives like 'assess_league_readiness' or 'classify_sport_archetype'. No when-not-to-use 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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