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Novarithm Agent Hub: trust and commerce checks

fact_verify

[PAID $0.002 USDC/call, x402, eip155:8453] Verifies a signed fact: pass the base64url canonical payload and its signature, receive valid true/false. For agents that stored a fact and must prove later that it was not altered.

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": {
      "payload": "<payload>",
      "signature": "<signature>"
    },
    "name": "fact_verify"
  }
}

Input Schema

NameRequiredDescriptionDefault
payloadYesbase64url of the canonical JSON (fact, source, measured_at, observed_at, value, query)
signatureYesbase64url Ed25519 signature returned with the fact

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description usefully discloses the payment model ($0.002 USDC per call via x402 on eip155:8453) and that the result is a boolean validity flag. It does not say what happens on a malformed payload or an unparseable signature (false versus an error), nor whether verification is local or remote, leaving the failure profile ambiguous.

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?

Two tight sentences with the cost/payment qualifier front-loaded and the purpose and return value immediately after. No filler, though the bracketed pricing prefix is dense metadata that partly competes with the core statement.

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 simple two-parameter read-style tool with no output schema, the definition covers inputs, output shape (valid true/false), and the paid-access requirement. The remaining gap is error semantics on invalid inputs, which is not negligible given that 'invalid signature' and 'malformed payload' could both look like a false result.

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 are fully described there, including the canonical JSON field list and the Ed25519 signature format. The description only restates the parameter roles at a higher level, adding no encoding nuances or round-trip pairing guidance beyond the schema.

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 ('Verifies a signed fact') plus the exact input pair and the boolean return, so an agent can tell what it does without opening the schema. It does not distinguish itself from nearby siblings such as certify_signed or verify_attestation, which also deal with signed/verified artifacts.

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?

Provides a clear usage scenario ('agents that stored a fact and must prove later that it was not altered'), which implies when to call it. However, it gives no exclusions and never names the alternative tools (certify_signed, verify_attestation, verify_delivery) that an agent must choose between in this crowded sibling set.

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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