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DanielTomaro13

sportsdata-mcp

oddsapiio_events

Read-onlyIdempotent

Get upcoming sporting events by sport or league, returning matchups and start times without odds. Requires an Odds API key.

Instructions

Upcoming events for a sport or league, without prices. NEEDS A KEY.

Returns: [{id, sport, league, home, away, starts, status}] — SHAPE FROM VENDOR DOCS.

NOTE: this shape is from the vendor's documentation and has NOT been verified against a live response (we hold no key for this provider). Treat it as approximate — inspect the actual payload before relying on a field name.

Example: Upcoming football {"sport": "football"}

Auth: needs your own key in ODDS_API_IO_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoYYYY-MM-DD.
sportNoSport slug.
leagueNoLeague id or name.
Behavior5/5

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

The description goes well beyond the read-only/idempotent annotations by disclosing authentication requirements (own key in ODDS_API_IO_KEY) and, most importantly, explicitly stating the return shape is from vendor docs and NOT verified against a live response. This caveat tells the agent to inspect actual payloads before relying on field names, a high-value behavioral warning.

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?

The description is well-structured into labeled sections: summary, return shape, caveat, example, and auth. It is slightly longer than strictly necessary but every sentence earns its place. The caveat and example are valuable, and the formatting aids readability.

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?

Given there is no output schema, the description compensates by listing the return fields and warning that the shape is approximate. It also covers authentication, parameter usage via example, and clarifies the tool's scope (no prices). For a simple read-only list tool, this is a complete and self-sufficient description.

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 100%, so the baseline is 3, but the description adds a concrete usage example ({"sport": "football"}) that illustrates how to pass the sport parameter. This extra example helps clarify the intended call structure, improving over mere schema descriptions.

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?

The description clearly states the tool returns 'Upcoming events for a sport or league, without prices.' This is a specific verb (retrieve/list) plus a concrete resource (events) and a distinguishing scope (sport/league, no prices). It also provides the return shape and an example, making the purpose unmistakable and differentiating it from odds-related siblings.

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?

The description gives clear context for when to use the tool (upcoming events without prices), implies exclusion (don't use if you need prices), and includes an example query. However, it never explicitly names an alternative tool like oddsapiio_odds, relying on implicit inference rather than direct guidance.

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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