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Dev Espn F1 Results

dev_espn_f1_results
Read-only

ESPN Formula 1 race list for one date with the finishing order of the first drivers (position, driver name, winner flag) and session state, from ESPN's public site JSON. Results only as ESPN lists them; a race with no published order returns the entries it has. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNoHow many finishers per race, 1 to 22 (default 10)
dateNoDate YYYY-MM-DD (default: yesterday UTC)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
countNo
racesNo
sourceNo
checkedAtNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Goes well beyond the readOnly/openWorld annotations by naming the data source (ESPN's public site JSON), disclosing partial-data behavior ('a race with no published order returns the entries it has'), and stating the exact cost model ($0.002 USDC per successful call via x402 on Base, Solana or Arc; failures not charged). Only rate limits/concurrency behavior are left unstated.

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-loads the resource and scope in the first clause, then adds data-source, edge-case, and pricing notes in dense but purposeful sentences. Slightly packed, but every sentence contributes information an agent would not otherwise have.

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 an output schema present, return structure needs no explanation, and the description covers source, partial-result handling, and payment. The only gap is what happens when no race exists on the given date, which the agent must infer.

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 both parameters carry ranges and defaults, so the schema does the heavy lifting. The description's mention of 'first drivers' loosely maps to the top parameter and describes per-entry fields, but that overlaps with the output schema rather than adding new parameter semantics.

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?

States a specific verb and resource: an ESPN Formula 1 race list for a single date with finishing order and session state. F1 is clearly distinguished from the other ESPN sport siblings by name, though the description never explicitly contrasts itself with sibling tools like dev_espn_nascar.

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?

Usage is only implied: call it with a date to get that day's F1 results. There is no statement of when to prefer this over dev_espn_sports/standings or other racing sources, and no prerequisites beyond the payment note.

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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