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DanielTomaro13

sportsdata-mcp

dabble_fixture_details

Read-onlyIdempotent

Retrieve the complete betting book for a single fixture from Dabble, including all markets, selections, prices, and player props. Use fixtureId to fetch detailed odds data for one match at a time.

Instructions

The FULL book for one fixture — every market (hundreds), all selections + prices, the marketGroups (SGM grouping) and the Pick'em playerProps product. LARGE (~1 MB+ for a major match); fetch one fixture at a time. fixtureId comes from dabble_competition_fixtures. Each market gets an engine-derived product: SGM legs by Dabble's capability flags (isSgmAllowed && !isSingleAllowed) so it's robust to the SGM vendor (SportCast today) changing; Pick'em by the pickem token (e.g. odds_on_pickem_goals) and racing by the Racing* resultingType — both first-party naming. RACING resultingTypes: RacingFixed*/RacingSP*=win/place, RacingDD*=exotics, RacingSrm*=Same-Race-Multi (no Pick'em in racing).

Returns: {sportFixtureDetail:{id, name, competitionName, sportName, status, teams, markets:[{id, name, resultingType, product, isSgmAllowed, isSingleAllowed}], selections:[{id, name, marketId}], prices:[{marketId, selectionId, price}], marketGroups, marketGroupMappings, playerProps:[{playerName, stats, value, lineType}]}} (LARGE — markets/selections/prices number in the hundreds-to-thousands. Each market carries an engine-derived product ∈ {single, sgm, pickem, srm, racing}: RacingSrm*→srm, Racing*→racing, resultingType-contains-pickem→pickem, else isSingleAllowed→single, else isSgmAllowed→sgm, else→single. Use product ∈ {single, sgm} for like-for-like price comparison; NEVER blend pickem multipliers into fixed-odds value/arb.)

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixtureIdYesFixture UUID (from dabble_competition_fixtures.data[].id). Required — part of the URL path.
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses the response size, the complete return structure, the engine-derived product classification logic (with precise rules based on capability flags and resultingType), and that no auth is needed. It also warns against blending pickem multipliers into fixed-odds calculations, adding valuable 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long and dense, but it is well-structured: the first sentence states the core purpose, and each subsequent paragraph addresses a specific aspect (size, product derivation, return shape, usage caution). It is not padded, but the sheer length prevents a perfect score for conciseness.

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 and only one parameter, the description fully compensates by specifying the exact return shape, the product classification rules, size warnings, and appropriate usage cautions. It gives an agent everything needed to correctly invoke and interpret the tool's results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% coverage for fixtureId, including its source (dabble_competition_fixtures) and that it is required. The description repeats this source but adds no new parameter-specific semantics, so it meets the baseline of 3 without exceeding it.

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 opens with 'The FULL book for one fixture' and explicitly enumerates the contents: every market, selections + prices, marketGroups, and Pick'em playerProps. This clearly states the tool's function (returns detailed fixture data) and distinguishes it from siblings like dabble_competition_fixtures, which likely only list fixtures.

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 tells the user that fixtureId comes from dabble_competition_fixtures and warns that the response is LARGE (~1 MB+), advising to fetch one fixture at a time. This provides clear usage context, but it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.

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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