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DanielTomaro13

sportsdata-mcp

apisports_football_odds

Read-onlyIdempotent

Retrieve pre-match football odds from multiple bookmakers for a specific fixture or league, enabling cross-bookmaker comparison.

Instructions

Pre-match odds from many bookmakers for a fixture or league.

Returns: {response:[{fixture, league, update, bookmakers:[{id, name, bets:[{id, name:'Match Winner', values:[{value:'Home', odd:'1.85'}]}]}]}]} — SHAPE FROM VENDOR DOCS. ODDS ARE STRINGS, not numbers. For AU markets the direct providers here (sportsbet, tab, pointsbet) are deeper and live.

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: One fixture's odds {"fixture": 1035037}

Auth: needs your own key in API_SPORTS_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
betNoOne bet/market id.
pageNoPaginated — check `paging.total`.
leagueNoLeague id (pair with season).
seasonNoSeason starting year.
fixtureNoOne fixture id.
bookmakerNoOne bookmaker id.
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses critical behavioral traits: the return shape is from vendor docs and unverified (no key held), odds are strings, and the actual payload should be inspected before relying on field names. This is honest and valuable context.

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 with sections for return shape, caveat, example, and auth. It is a bit long, but every part adds necessary value, especially the unverified-shape warning. The front-loaded purpose is effective.

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?

With no output schema, the description must convey the return structure, which it does with an explicit shape example. It also covers auth, parameter usage via example, and the reliability caveat. This is complete for a read-only odds tool with an approximate vendor schema.

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%, providing baseline 3. The description adds an example using 'fixture' and explains the two main query modes (fixture or league), which enriches parameter understanding beyond the schema's per-field descriptions.

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 clearly states the tool returns 'Pre-match odds from many bookmakers for a fixture or league', which identifies both the resource and the scope. It differentiates from sibling tools by focusing on odds and pre-match, but lacks an explicit imperative verb like 'retrieve'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: 'For AU markets the direct providers here (sportsbet, tab, pointsbet) are deeper and live.' This names alternatives and the condition for preferring them over this tool, which is exactly the kind of when-to-use vs alternatives guidance needed.

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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