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predgeAI

whale-data-mcp

by predgeAI

Sports outcome attestation — signed settled game result (flagship)

predge_sports_attest

Verify settled sports outcomes with Ed25519-signed ESPN results for a finished match. Settle bets or prove track records offline by checking the signature against Predge's public key.

Instructions

PAID (~$0.02). Ed25519-SIGNED settled game outcome for one finished match — winner, final score, completed(bool), teams, scheduled time — sourced from ESPN and signed with Predge's published key, so it VERIFIES OFFLINE (no trust in this API): re-check the signature against the pubkey at data.predge.io/.well-known/predge-attest.json. Use it to settle bets, prove a track record, or ground a wager on a tamper-evident result. Optional winner (team abbreviation e.g. 'LAL'): adds queried_winner and correct (true iff it matches the settled winner). Unknown league or unfinished/unknown event returns null and is NOT charged. Leagues: nba, wnba, nfl, college-football, mlb, nhl, mls, epl, champions-league, laliga. Params: league, event_id (provider event id), winner.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
leagueYes
winnerNo
event_idYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the payment cost (~$0.02), offline verifiability, signing key location, and the null/not-charged behavior for unknown events. This goes beyond basic transparency, though it could mention rate limits or response format details.

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?

The description is a single dense paragraph but front-loads key facts (PAID, SIGNED, OFFLINE). Every sentence contributes meaningful details; however, it could be more structured with bullets for readability.

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?

Given no output schema, the description covers return behavior (null for unknown/unfinished), the winner parameter's effect (queried_winner and correct), and the data fields returned. It does not specify the exact response structure (JSON shape or signature format), but it provides sufficient context for basic usage.

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?

Schema description coverage is 0%, so the description must define each parameter. It explains league (with enum list), event_id (provider event id, pattern hints), and winner (team abbreviation, optional, adds queried_winner and correct). It also explains that unknown league/event yields null, which adds semantic value beyond the schema.

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 clearly states the tool's purpose: it provides a signed settled game outcome for one finished match, including winner, final score, completed flag, teams, and scheduled time. It specifies the source (ESPN) and the signing (Ed25519), and it distinguishes itself from siblings by emphasizing offline verification and sports-specific attestation.

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?

The description gives concrete use cases: settle bets, prove track record, ground a wager. It also notes the boundary that unknown/finished events return null and are not charged. However, it does not explicitly contrast with sibling attest tools (e.g., kalshi_attest, wallet_attest), but the sports-specific focus makes it clear enough.

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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