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by net.crawlora
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nascar_live_feed

Read-only

Get NASCAR's latest published global session feed and return the native race id, run id and series id together with track and lap metadata, timestamps, flags and every vehicle row with its driver id, full name and car number. This feed takes no selectors or parameters: it returns whichever session was published last (possibly a completed one), never a promise of a currently running race and never a Cup-only filter. It is one public anonymous JSON feed with no upstream key, cookie or selector.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nascar_live_feed"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

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
Behavior4/5

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

Beyond the supplied readOnlyHint/openWorldHint annotations, it discloses that the feed is public and anonymous with no upstream key, cookie or selector, and that freshness is not guaranteed ("never a promise of a currently running race"). That is genuinely useful context, though it does not describe volume, pagination, or behavior when no session exists.

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?

Three sentences, front-loaded with the return shape followed by scope caveats, and no filler. The first sentence is long and clause-dense, but each clause carries distinct information.

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 zero-parameter read feed with an output schema and annotations, the description covers what is returned, what is not filtered, freshness semantics, and auth requirements. 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.

Parameters4/5

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

With zero parameters and 100% schema coverage, the baseline is already high. The description reinforces this by explicitly stating the feed "takes no selectors or parameters," which prevents an agent from inventing filter arguments.

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 a specific verb and resource ("Get NASCAR's latest published global session feed") and enumerates the returned entities (race id, run id, series id, track/lap metadata, vehicle rows), so an agent knows exactly what this returns. It also pre-empts confusion with sibling race-listing tools by stating it is "never a Cup-only filter."

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 gives clear conditions for use: the feed takes no selectors, returns whichever session was published last, and may be a completed session rather than a live one. Those are meaningful usage constraints, but it never names an alternative tool (e.g. nascar_races) for filtered or Cup-specific queries, leaving the agent to infer that routing.

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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