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nba_team_on_off

Read-only

Get Returns a team's on-court/off-court player splits: the on-court and off-court rows the upstream computes, with each player's minutes and rating impact. Returns a team's on-court/off-court player splits: the on-court and off-court rows the upstream computes, with each player's minutes and rating impact.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nba_team_on_off"
  }
}

Input Schema

NameRequiredDescriptionDefault
seasonNoOptional season in YYYY-YY form; defaults to the current NBA season.
team_idNoRequired team id from nba-standings.
per_modeNoOptional aggregation; defaults to PerGame.
league_idNoOptional league id; only 00 (NBA) is verified.
season_typeNoOptional season type.
measure_typeNoOptional statistic family; defaults to Base.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful context that output consists of upstream-computed on-court and off-court rows with minutes and rating impact. It says nothing about data freshness, required permissions, or rate limits beyond the annotations.

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

Conciseness2/5

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

The single sentence is repeated verbatim twice, which is pure waste, and the text opens with the malformed fragment 'Get Returns'. Beyond deduplication there is no structure to speak of.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the annotations cover the read-only profile. Still, for a six-parameter tool sitting among many similar team-split siblings, the absence of any routing guidance leaves the definition only minimally complete.

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 100%, so all six parameters (season, team_id, per_mode, league_id, season_type, measure_type) are already documented in the schema, including that team_id must come from nba-standings. The description adds no parameter meaning beyond that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource and output shape: a team's on-court/off-court player splits, with each player's minutes and rating impact. An agent can tell it produces player-level on/off rows. It does not, however, differentiate itself from the many nba_team_dash_* siblings that also return team splits.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no exclusions, and no named alternative. The agent is left to infer from the name alone whether this is preferable to nba_team_dash_by_game_splits, nba_team_stats, or nba_box_score_usage.

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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