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DanielTomaro13

sportsdata-mcp

tab_racing_race

Get full racecard for a single race, including runners with fixed and parimutuel odds, form ratings, pools, bet types, and results with dividends after the race.

Instructions

Full racecard for one race: runners with fixed + parimutuel odds, form ratings, pools, bet types; results + dividends once run.

Returns: {raceNumber, raceName, raceDistance, raceStartTime, runners:[{runnerNumber, runnerName, fixedOdds, parimutuel, riderDriverName, barrierNumber, last5Starts}], results, pools, betTypes, multiLegApproximates}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes
raceTypeYes
raceNumberYes
jurisdictionNoNSW
venueMnemonicYes
Behavior3/5

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

With no annotations, the description must convey behavioral traits. It notes that results and dividends are available only after the race is run, which is useful. However, it does not disclose potential side effects, required permissions, or rate limits. The return structure is detailed but behavioral implications beyond data content are omitted.

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

Conciseness5/5

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

The description is exceptionally concise, using two well-structured sentences. The first sentence summarizes functionality, and the second lists return fields. There is no redundancy or wasted words, making it easy to parse quickly.

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

Completeness2/5

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

Given the tool has 5 parameters, no output schema, and many racing-related siblings, the description is insufficiently complete. It does not explain how to construct a request or interpret results in context. Key details like parameter meanings and result usage are missing, leaving the agent underinformed.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no information about the parameters (date, raceType, raceNumber, jurisdiction, venueMnemonic). It does not explain expected formats, allowed values, or how to use them to retrieve a specific race. This is a critical gap.

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 a full racecard including runners, odds, form, pools, bet types, and results. It specifies pre-race and post-race data, making the purpose evident. However, it does not explicitly differentiate from similar siblings like tab_racing_race_form or sportsbet_racecard, which also provide race data.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description lacks explicit context about scenarios where this tool is preferred or when other racing tools should be used. There is no mention of prerequisites or exclusion criteria.

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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