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McNews11

euroleague-open-data

by McNews11
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

get_draft_board

Rank EuroLeague players for fantasy drafts using value over replacement, highlighting the best available option at each position given league size and roster limits.

Instructions

Rank players for a BasketNews Fantasy DRAFT by value over replacement.

Use this for "who should I pick", "best available guard", or any draft ordering
question. Do NOT rank by points per game for a draft: every manager gets a unique
roster, so what matters is how much better a player is than the next player at the
SAME position who will still be available. That is `vorp_per_game`, and it is the
correct sort order.

Scoring is the BasketNews modern system, recomputed exactly from boxscores.

Fields worth reasoning about:
  vorp_per_game     - value over replacement. The draft ranking.
  modern_per_game   - raw fantasy average.
  modern_floor_p25  - bad-night floor. Matters more in a draft than in a budget
                      league, because you keep the pick all season.
  consistency_ratio - mean divided by standard deviation. Higher is steadier.
  replacement_level - what is still gettable at this position late in the draft.

Args:
    season: season code, e.g. "E2025".
    teams: managers in the league, 3-12. This changes replacement level and therefore
        the ranking, so ask the user if it is unknown. BasketNews recommends 7-8.
    roster_size: players per roster. BasketNews draft mode is 13.
    position: optional filter, "Guard", "Forward" or "Center".
    min_games: exclude players below this many appearances.
    limit: rows to return.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
teamsNo
seasonNoE2025
scoringNoclassic
positionNo
min_gamesNo
roster_sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.5/5.0
Behavior4/5

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

No annotations are present, so the description carries the burden. It discloses the ranking methodology, the fact that scoring is recomputed from boxscores, and how teams affect replacement level. However, it does not explicitly state that this is a read-only operation, and there is a slight inconsistency regarding the scoring parameter (schema default 'classic' vs. description's 'modern system'), though this may reflect different aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections for usage, fields, and arguments. It front-loads the core purpose and keeps explanations relevant. Slightly verbose, but each sentence provides useful context for an agent.

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?

The tool has 7 parameters and an output schema. The description explains the ranking logic and key fields, making it complete enough for most draft-related tasks. It could be improved by explicitly mentioning the scoring parameter's effect and clarifying read-only behavior, but overall it covers the complex domain well.

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 description adds meaningful context for all schema parameters except 'scoring'. It explains the impact of 'teams' on replacement level, what 'roster_size' means, and the fields returned. The omission of the 'scoring' parameter is a gap, especially since the description claims a specific scoring system while the schema allows a different default.

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 opens with a specific verb and resource: 'Rank players for a BasketNews Fantasy DRAFT by value over replacement.' It clearly distinguishes the tool from siblings like search_players or compare_draft_candidates by focusing on draft ordering, not generic stats.

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?

Provides explicit guidance: 'Use this for...', 'Do NOT rank by points per game for a draft', and explains why via the unique-roster rationale. It also advises asking the user if the teams count is unknown, making the usage boundaries clear.

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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