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McNews11

euroleague-open-data

by McNews11

compare_draft_candidates

Compare two or more players to decide your fantasy draft pick. Get season stats and replacement-level context from EuroLeague data to choose the better option.

Instructions

Compare named players side by side for a draft pick decision.

Use when the user is choosing between specific players ("Vezenkov or Milutinov?").
Resolve names to person_codes with search_players first.

Args:
    person_codes: two or more canonical ids.
    season: season code, e.g. "E2025".
    teams: managers in the league, used to set replacement level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamsNo
seasonNoE2025
scoringNoclassic
person_codesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

There are no annotations, so the description carries the full burden. It explains the role of the 'teams' parameter (setting replacement level) and notes that person_codes should be 'two or more,' providing some behavioral detail. However, it does not disclose what the comparison output contains (despite an output schema existing), how it handles missing or invalid codes, or any other side effects. The information given is helpful but not comprehensive.

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 tight and front-loaded: a one-sentence purpose, a one-sentence usage guideline, and a concise args list. Every sentence adds value with no redundancy. The structure is easy to scan.

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 that an output schema exists, the description need not explain return values. It covers the primary purpose, usage context, required parameter, and key optional parameters. The missing explanation of 'scoring' is a minor gap, but overall the description gives an agent enough context to select and invoke the tool correctly.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It explains person_codes, season, and teams: person_codes are 'canonical ids' (two or more), season has an example code, and teams is 'managers in the league, used to set replacement level.' It omits the 'scoring' parameter entirely, leaving it undocumented. Thus, partial semantic coverage.

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 action: 'Compare named players side by side for a draft pick decision.' It specifies the resource (players) and the context (draft pick decision), distinguishing it from siblings like get_player_fantasy_log or plan_snake_draft. The example 'Vezenkov or Milutinov?' further clarifies the intended use.

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

Usage Guidelines5/5

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

The description explicitly says 'Use when the user is choosing between specific players' and provides an example query. It also gives a clear prerequisite: 'Resolve names to person_codes with search_players first.' This directly informs the agent when and how to invoke the tool, including the need to pre-process names.

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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