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Money Mind — the judge

Money Mind — Fact Check: verify a claim against sources — $0.03 per call

factcheck
Read-only

Verify a claim against 2-4 source URLs: cited passages, cross-source agreement, verdict: consistent | conflicting | insufficient_evidence. Evidence, not truth. Use when your agent needs to verify a claim against independent sources before acting on it. Give a claim plus 2-4 source URLs; each source is extracted (three-fetch cross-check, confidence-scored), the checkable figures are compared across sources, and you get the cited passages plus a verdict: con PAID: $0.03 USDC on Base via x402. Call it to receive the payment challenge. Example request: {"claim": "Acme Corp revenue was $4.2 billion in 2025", "urls": ["https://example.com", "https://example.org"]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesexample: ["https://example.com", "https://example.org"]
claimYesexample: "Acme Corp revenue was $4.2 billion in 2025"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/non-destructive, so the safety profile is covered. The description adds substantive behavior beyond that: the three-fetch cross-check with confidence scoring, cross-source figure comparison, and crucially the paid model ($0.03 USDC on Base via x402) with the payment-challenge handshake, which is essential context for invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core (claim + 2-4 URLs in, passages + verdict out) is front-loaded, but the text is a run-on with a garbled/truncated segment ('...verdict: con PAID: $0.03 USDC...') where sentences collide, hurting 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?

For a 2-param tool with no output schema, the description covers inputs, processing, return values, verdict vocabulary, and the payment model. The only shortfall is the missing explanation of the output field shape, which is partly implied by the listed verdict values.

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 coverage is 100%, so baseline is 3, but the schema 'descriptions' are only bare examples, whereas the description adds a real constraint (2-4 URLs, not arbitrary) and a full example request payload, giving meaning the schema does not.

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 (verify) and resource (a claim against 2-4 source URLs) and enumerates the outputs: cited passages, cross-source agreement, and a verdict enum. It is clearly distinguishable from statistical siblings like correlation or abtest.

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?

Explicitly states the context: 'Use when your agent needs to verify a claim against independent sources before acting on it.' It also tells the caller the payment flow ('Call it to receive the payment challenge'). It does not name any sibling alternative, but none of the siblings share this function.

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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