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stat-api — Sports Data

Get record

get_record
Read-onlyIdempotent

Fetch a single row by primary key. Returns the row object. Requires a stat-api sign-in or API key; costs 1 record of quota.

Input Schema

NameRequiredDescriptionDefault
idYesprimary-key value (integer or text PK)
tableYes
leagueYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / league / enum
      Previous value: -[
      -  "nfl",
      -  "nba",
      -  "mlb",
      -  "nhl",
      -  "pga",
      -  "dfs",
      -  "kalshi",
      -  "polymarket",
      -  "reference"
      -]New value: +[
      +  "nfl",
      +  "nba",
      +  "mlb",
      +  "nhl",
      +  "pga",
      +  "dfs",
      +  "reference"
      +]
  2. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered elsewhere. The description adds genuinely new behavioral context: authentication requirements and a quota cost, plus the return shape. It stops short of detailing error behavior for missing keys.

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?

Three short sentences, front-loaded with the core action, then the return value, then the operational constraints. Nothing is wasted or repeated from the schema.

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?

With no output schema, the description helpfully states that the row object is returned, and it covers auth and quota. The main remaining gap is the unspecified semantics of 'table' and 'league', though sibling tools (list_tables, list_leagues) can supply those values.

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?

Schema coverage is only 33% -- just 'id' is documented, while 'table' and 'league' (an enum of seven leagues) have no descriptions anywhere. The description mentions 'primary key' but adds no syntax, format, or guidance for selecting table/league, so the gaps are not compensated.

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 gives a specific verb and resource ('Fetch a single row by primary key') and states the return shape ('Returns the row object'). It distinguishes the tool implicitly from query_table/describe_table by emphasizing single-row primary-key lookup, but never names an alternative explicitly.

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

Usage Guidelines3/5

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

It states prerequisites (stat-api sign-in or API key) and cost (1 record of quota), which is useful selection context. However, there is no explicit when-to-use-this-vs-siblings guidance, e.g. versus query_table or search_players, so usage is only implied by 'by primary key'.

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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