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NBA injury report

invoke_nba_injuries
Read-onlyIdempotent

NBA injury report with an impact score from 1 to 10: player, team, position, status, injury note, estimated return, games missed in a row, DK points, minutes, usage, points, rebounds and assists per game, whether the absence is priced in, a new-team flag, and the teammates who gain the minutes and usage. Sorted by impact. Data refreshes every 30 minutes.

Input Schema

NameRequiredDescriptionDefault
teamNoTeam abbreviation, for example LAL or BOS.
limitNoMaximum rows to return. The plan limit applies on top.
playerNoPlayer name, or part of a name.
statusNoStatus filter, for example Out or Questionable.
min_impactNoLeast impact score, 1 to 10.
plays_todayNoOnly teams that play today.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, and the description adds genuinely useful behavior: results are sorted by impact and data refreshes every 30 minutes, which affects caching/staleness decisions. It omits rate limits and the concrete 'plan limit' interaction hinted at in the limit parameter.

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?

Purpose and impact-scoring concept are front-loaded in the first clause, followed by a dense field inventory and the refresh note. It is one long sentence, but with no output schema the field list earns its space; only the trailing teammate clause feels slightly padded.

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?

With no output schema, the description carries the return-value burden and does so thoroughly, listing every field plus sort order and refresh interval. The remaining gap is usage context — when an agent should prefer this over the other NBA tools — but the payload description is 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 filters (team, limit, player, status, min_impact, plays_today) are already documented, setting the baseline at 3. The description's 'impact score from 1 to 10' reinforces the min_impact semantics but adds no new filter syntax or default behavior.

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 the resource (NBA injury report) and enumerates the exact payload — impact score 1-10, player, team, status, DK points, usage, priced-in flag, teammates who gain minutes — which makes the tool's output unmistakable. It is clearly distinct from stat siblings like invoke_nba_projections or invoke_nba_foul_risk, though it never explicitly names those alternatives.

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 statement of what question this answers, no exclusions, and no reference to the many adjacent NBA siblings (invoke_nba_rotations, invoke_nba_projections, invoke_nba_foul_risk). The 'priced in' field hints at DFS lineup use but the agent must infer it. Only the refresh cadence gives any operational context.

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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