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dohyung1

FPL Intelligence

league_analyzer

Analyze any mini-league to predict the winner using points gap, squad quality, chips remaining, recent form, team value, and injury concerns. Input a league ID for win probabilities of top managers.

Instructions

Predict who will win a mini-league based on current form, squad quality, and chips remaining.

USE THIS WHEN the user asks: "Who's going to win my league?", "League predictions",
"Who's the favourite?", "Analyze league standings", "Win probability", or any question
about league-wide chances WITHOUT needing a specific team ID.

Does NOT require the user's team ID — just the league ID. Analyzes the top managers
in the league and calculates win probability for each based on: points gap, squad quality,
chips remaining, recent momentum, team value, and injury concerns.

The league ID is in the mini-league URL: fantasy.premierleague.com/leagues/LEAGUE_ID/standings/c

Args:
    league_id: Mini-league ID from the league URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
league_idYes
Behavior3/5

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

The description discloses the factors considered (points gap, squad quality, chips, etc.) and that it doesn't require team ID, but lacks details on output format or any limitations, and there are no annotations to provide additional context.

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 concise, well-structured with purpose, usage guidance, and args clearly separated. Every sentence contributes meaning without redundancy.

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 tool with one simple parameter and no output schema, the description covers purpose, usage, and parameter meaning adequately. Missing details on the format of the prediction output, but overall sufficient.

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

Parameters5/5

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

The schema has zero description coverage for the single parameter, but the description fully explains the 'league_id' parameter, including where to find it in the URL, adding significant value beyond the bare 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 explicitly states it predicts mini-league winners based on specific factors, lists example user queries, and implicitly distinguishes from sibling tools by noting it doesn't require a team ID.

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 provides explicit usage triggers like 'USE THIS WHEN the user asks...' and clarifies that no team ID is needed, but does not mention when not to use or suggest alternatives.

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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