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NBA pace and possessions

invoke_nba_pace
Read-onlyIdempotent

NBA pace for today, calculated by BankrollSZN from box scores. Possessions per 48 minutes (overtime removed). view games (default) gives each game today with projected pace, the gap to the league average (vs_league), a tier (Up, Neutral, Slow), a flag when the market total and the pace disagree, the total, spread and moneylines, both teams' pace ratings and ranks, and actual pace once played. view teams gives all 30 teams: pace rating (half season, half last 10), season, last 10 and last 5 pace, last season pace, offensive, defensive and net rating, combined points per game and rank. Data refreshes every 30 minutes.

Input Schema

NameRequiredDescriptionDefault
teamNoTeam abbreviation, for example LAL or NY.
tierNogames view: only this tier.
viewNoDefault games.
limitNoMaximum rows to return. The plan limit applies on top.
sort_byNoteams view sort. Default rank.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds genuine context the annotations cannot: the data source (box scores), the definition of pace with overtime removed, and a 30-minute refresh cadence. It does not mention auth requirements or pagination behavior.

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?

Front-loaded with the core definition, then a dense but substantive enumeration of return fields. Given there is no output schema, the field listing earns its place, though the single run-on paragraph could be split for scanability.

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?

With no output schema, the description carries the full burden of describing return values, and it does so thoroughly for both views. Combined with the refresh cadence and pace definition, an agent has everything needed to call it correctly.

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?

Schema coverage is already 100%, so baseline is 3, but the description adds meaning beyond the schema labels: it defines what the 'tier' enum values (Up/Neutral/Slow) represent, what each 'view' returns, and that sort_by applies to the teams view. This is real added value over bare enum lists.

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?

States a specific resource (NBA pace/possessions for today), the computation method (from box scores, possessions per 48 minutes with overtime removed), and the source. An agent can immediately distinguish this from invoke_nba_projections, invoke_nba_rotations, or invoke_nfl_pace.

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?

Clearly explains the two operating modes and what each returns, letting the agent pick 'games' (default, per-game pace vs market totals) or 'teams' (all 30 teams with ratings). It does not, however, say when to reach for this tool instead of related NBA siblings such as projections or sim_picks.

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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