Get injury report
get_injury_reportCurrent injury report for a team.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| team | Yes |
get_injury_reportCurrent injury report for a team.
| Name | Required | Description | Default |
|---|---|---|---|
| team | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds only the word 'Current' to convey freshness/temporal scope. No further behavioral detail (e.g., whether historical reports are available or how recent the data is) is disclosed, but the annotations carry the main burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundancy or filler. It immediately states the resource and scope, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is simple (one parameter, read-only annotations), the description is minimally adequate: it names the resource and the parameter's role. However, without an output schema or any detail about the report's structure, and no link to sibling list_teams for valid team values, an agent may not know how to correctly invoke it or interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the only parameter 'team' has no description in the schema. The phrase 'for a team' clarifies that the team parameter refers to the team of interest, but it doesn't specify the expected format (name, abbreviation, ID), valid values, or how to obtain team identifiers. This is minimal compensation for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb-implied action ('Current injury report') and a specific resource ('for a team'), making it unambiguous what the tool returns. It is distinct from sibling tools like get_roster or get_player_stats, as an injury report is a different data category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: an agent should call this when it needs current injury information for a team. However, no explicit alternatives, exclusions, or conditions are provided. It doesn't mention that team identifiers might come from list_teams, so the guidance is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource: injuries, odds, player stats, roster, schedule, and the universe of teams. There is no overlap or ambiguity between them.
All tools use a clear verb_noun pattern: get_* for specific resources and list_teams for the full collection. This is consistent and predictable.
Six tools is well-scoped for a read-only sports data server covering NFL and NBA information. Each tool covers a meaningful slice of the domain without bloat.
The surface covers the main pre-game and season data needs: teams, rosters, schedule, stats, injuries, and odds. Only a minor gap exists for something like game results or standings, which is not central to the apparent betting/team-info focus.