MCPFax Reliability

Wallet authenticity and wash-risk

mcpfax_wallet_authenticity

Read-onlyIdempotent

Payer-concentration and wash-risk assessment for a receiving wallet: how concentrated its observed payers are, the measured coverage of that observation, an explicit wash-risk haircut ONLY when coverage is sufficient, how many listings declare the same address, and observed USDC inflow. Use this to judge whether a seller's apparent revenue reflects real independent demand. The haircut and the adjusted-inflow figure are withheld as null with status "not_rated" until the wallet's own record covers at least 14 days and 20 payments, because below that a thin payer count is a property of our observation window, not of the wallet. Concentration is not proof of common control. Costs $0.01 USDC per call via x402 on Base.

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": {
      "wallet": "<wallet>"
    },
    "name": "mcpfax_wallet_authenticity"
  }
}

Input Schema

Name	Required	Description	Default
`wallet`	Yes	The receiving EVM wallet address, 0x followed by 40 hex characters, e.g. '0x1831f336585a6C67B6A954d28f3E07F44C4EEBbd'.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 4, 2026
- addedInput schema / properties / wallet / examples
```
Added value: +[
+  "0x1831f336585a6C67B6A954d28f3E07F44C4EEBbd"
+]
```
First observedAug 14, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the readOnlyHint/idempotent annotations, the description discloses important conditional behavior: the haircut and adjusted inflow are null with status 'not_rated' until 14 days and 20 payments are observed, with a rationale. It also states the $0.01 USDC fee via x402 and the caveat that concentration is not proof of common control. This is rich, useful transparency.

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

Conciseness5/5

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

Every sentence carries load-bearing information: definition, use case, null-status condition and rationale, caveat, and cost. The most important framing is front-loaded, and there is no filler.

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?

With only one parameter and no output schema, the description still enumerates the key result elements, explains when outputs are withheld, and clarifies interpretation limits. An agent can predict both invocation and expected response shape well enough to use the tool correctly.

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%, so the schema already fully documents the single 'wallet' parameter including format and an example. The description adds context that the wallet is a 'receiving' wallet and that calls happen on Base, but it does not need to compensate for schema gaps. Baseline 3 is appropriate.

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-object statement: 'Payer-concentration and wash-risk assessment for a receiving wallet,' then enumerates the concrete outputs (concentration, coverage, haircut, listings, USDC inflow). This clearly distinguishes it from revenue or credit scoring siblings even without naming them.

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 provides a direct use case: 'Use this to judge whether a seller's apparent revenue reflects real independent demand.' This gives the agent clear context for when to invoke the tool, though it does not explicitly mention sibling tools or state when not to use it.

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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