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by net.crawlora
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nascar_race_weekend

Read-only

Get one NASCAR race weekend's complete native data: every weekend_race row with its results, plus the native practice/qualifying weekend_runs rows with their run ids, names, types, timing and source result values. season, series and race are native resource keys from nascar_series and nascar_season_races; the race must belong to the selected season and series, so cross-series or absent ids are a 404 instead of silently resolving another event. Native zero/empty values and timestamps stay source values and no completion, ranking or timezone is inferred. Driver hometown and biological fields are omitted. Membership validation reuses the five-minute annual metadata cache, and the weekend read itself is one anonymous JSON feed with no upstream key or cookie.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "season": "<season>",
      "series": "<series>",
      "race": "<race>"
    },
    "name": "nascar_race_weekend"
  }
}

Input Schema

NameRequiredDescriptionDefault
raceYesRequired source race ID from the selected season feed (nascar_season_races) in that series group. A race that is absent from the selected season/series is a 404 rather than another event.
seasonYesRequired four-digit native calendar year of the race.
seriesYesRequired source series ID from nascar_series for that season, for example 1 for the first native series group.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnly/openWorld annotations it discloses a lot: absent or cross-series ids return 404 rather than silently resolving another event, native zero/empty values and timestamps are preserved with no inferred completion, ranking or timezone, driver hometown and biological fields are omitted, membership validation reuses a five-minute annual metadata cache, and the read is one anonymous JSON feed needing no key or cookie.

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?

Front-loaded with the returned data, then the key/validation rules, then behavioral caveats – a sensible order. The prose is dense with long multi-clause sentences and repeats some schema content, but no sentence is filler.

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?

For a three-parameter read with full schema coverage, annotations and an output schema, the description covers identity, parameter provenance, failure mode, data-fidelity rules, field omissions and auth/caching behavior. Nothing an agent needs in order to call it correctly is missing.

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?

Schema coverage is 100% and each parameter already documents its source feed and the 404 condition, so the description's parameter sentence largely restates the schema. It adds only the framing of 'native resource keys' and the season/series membership constraint, which the schema already conveys.

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?

States a specific verb and resource ('Get one NASCAR race weekend's complete native data') and enumerates the payload: weekend_race rows with results plus weekend_runs practice/qualifying rows with run ids, names, types, timing and source values. This distinguishes it from race-list siblings like nascar_season_races and nascar_races without needing their schemas.

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?

Gives clear preconditions – season, series and race are native keys sourced from nascar_series and nascar_season_races, and the race must belong to that season/series or it is a 404. It does not name an alternative tool to use for cross-series or aggregate lookups, so there is no explicit when-not guidance beyond the 404 rule.

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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