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DanielTomaro13

sportsdata-mcp

dabble_fixture_details

Retrieve complete fixture details from Dabble including all markets, selections, prices, market groups, and player props for in-depth odds analysis and cross-provider comparison.

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.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixtureIdYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses large data size (~1 MB+), explains engine-derived product types and their derivation, and warns against blending pickem multipliers. Lacks rate limit or auth info, but the behavioral details are rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is quite long and dense, but well-structured: purpose, size warning, product derivation, return structure. Every sentence adds value, but it could be more concise by separating detailed product explanation from the main purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of the return data and the absence of output schema, the description includes a partial return type and explains key derived fields. It covers major aspects, though some nested structures like marketGroupMappings are not detailed. Provides reasoning for product assignment.

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

Parameters2/5

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

Only one parameter (fixtureId) with no schema description (coverage 0%). The description only states its source (dabble_competition_fixtures) but does not explain format, constraints, or type beyond the schema declaration. Minimal added meaning.

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 the full book for one fixture including all markets, selections, prices, marketGroups, and playerProps. It distinguishes from siblings like dabble_competition_fixtures by specifying this tool is for detailed fixture data, not just list of 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?

It explicitly states to fetch one fixture at a time, that fixtureId comes from dabble_competition_fixtures, and provides guidance on using product field for price comparison. It does not mention when not to use, but the context is clear.

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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