list_sports
Map the 13 covered sports to sport_id values before calling the odds tools. Does not consume API quota.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Map the 13 covered sports to sport_id values before calling the odds tools. Does not consume API quota.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the operational detail that the tool does not consume API quota, which goes beyond the readOnlyHint annotation and addresses rate-limit concerns. It also specifies the exact number of covered sports, giving concrete behavioral context.
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?
Two short sentences deliver the purpose, usage timing, and a behavioral note with no wasted words. The key mapping purpose is front-loaded before the quota note.
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?
For a zero-parameter, read-only tool with no output schema, the description provides enough information for an agent to know when and why to call it. The mapping to sport_id values and the prerequisite relationship to odds tools make the tool fully understood.
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?
The tool has zero parameters, and the schema coverage is 100%, so there is no parameter information needed. The description appropriately focuses on the tool's purpose rather than parameter details.
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 clearly states a specific verb and resource: mapping the 13 covered sports to sport_id values. It distinguishes the tool from sibling odds tools by positioning it as a prerequisite mapping step, so an agent can immediately understand its role.
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 explicitly says to use this tool 'before calling the odds tools,' providing clear context for when it should be invoked. It does not mention alternatives or exclusions, but none of the sibling tools appear to offer the same mapping functionality.
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.
get_live_odds and get_prematch_odds are clearly separated by live vs prematch, but get_prematch_lines, get_prematch_odds, and get_event all deal with prematch/event odds and could be confused. The descriptions clarify one-sport vs one-event vs full-detail scopes, but the boundaries require careful reading.
Most tools follow a clean get_<object> pattern (get_live_odds, get_prematch_odds, get_drops, get_event, get_health), and casing is consistent. list_sports breaks the pattern by using a different verb, and get_event/get_drops are slightly more generic than their odds-specific siblings, but overall the naming is predictable.
Seven tools is well-scoped for a focused odds-and-drops API. Each tool maps to a distinct need: sport mapping, live odds, prematch odds, event detail, price drops, and health/status, with no obvious fat to trim.
The core read-only odds surface is well covered: sports discovery, live and prematch odds, per-event detail, drops, and feed health. The main gap is that no-vig fair prices are only exposed through the drops tool rather than being available as a consistent property across all odds endpoints.