Get live odds
get_live_oddsLive betting markets for a team's next game: moneyline, spread, total with $1-payout math (NFL live now; NBA opens with the season).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| team | Yes |
get_live_oddsLive betting markets for a team's next game: moneyline, spread, total with $1-payout math (NFL live now; NBA opens with the season).
| 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 establish read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context: scope is limited to the next game, the markets offered, the $1-payout math convention, and league availability. It doesn't mention update frequency or out-of-season behavior, but this is acceptable given annotation coverage.
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 compact, information-dense sentence with no filler. The core purpose is front-loaded, and the parenthetical adds valuable league availability context without diluting the main message.
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 a single parameter, safety annotations, and no output schema, the description does enough to guide selection and invocation: it names the resource scope, market types, payout convention, and league availability. It could be more explicit about return formatting and empty/error states, but the main payload is already sketched.
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?
With 0% schema description coverage, the description must define the 'team' parameter, and it does clarify that team refers to the team whose next game odds are returned. However, it doesn't specify whether team should be a name, abbreviation, or ID, nor does it point to list_teams for valid values, leaving some ambiguity.
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 exactly what the tool returns: live betting markets (moneyline, spread, total) for a team's next game. This resource domain is clearly distinct from all sibling tools, which cover injuries, stats, rosters, schedules, and team lists.
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 description gives clear context for when to use the tool: when live odds for a team's upcoming game are needed. It also adds league availability timing ('NFL live now; NBA opens with the season'). It does not explicitly name alternatives, but the sibling tools are in unrelated domains, so the intended use is clear.
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.