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wallet_audit

Returns a heuristic high/medium/low address risk tier, named flags, ETH balance, holdings of 4 major tokens (USDC, WETH, cbBTC, DAI), and the Base EVM account nonce. Per-token risk is unknown because token contracts are not audited here. For EOAs the nonce counts outgoing transactions only, not full history. Address type is reported separately and does not affect the balance/nonce-based risk tier. Use to screen an address before paying it. Costs $0.02 in USDC on Base per successful call, paid with x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesBase chain wallet address, 0x-prefixed 20-byte hex

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

With annotations present, the bar is lower, yet the description adds substantial context beyond them: it discloses the cost ($0.02 USDC on Base per successful call, paid via x402), which also explains the readOnlyHint=false annotation; it states per-token risk is unknown because token contracts are not audited; and it clarifies that the EOA nonce counts outgoing transactions only. These are exactly the kind of operational caveats structured fields cannot carry.

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 return payload is front-loaded and every sentence contributes (payload, limitations, address-type caveat, use case, cost). It is dense but not padded, though the six sentences push toward the longer side for a one-parameter tool.

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?

There is no output schema, so the description must describe return values — and it does comprehensively (risk tier, flags, balances, nonce, address type). It also covers cost, model limitations, and risk-tier basis, leaving nothing an agent needs to invoke it correctly unstated.

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?

There is a single parameter with 100% schema description coverage ('Base chain wallet address, 0x-prefixed 20-byte hex'), so the schema already carries the semantics. The description adds no format or constraint detail for the address parameter. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

The description names the exact resource and payload: a heuristic high/medium/low risk tier, named flags, ETH balance, four specific token holdings (USDC, WETH, cbBTC, DAI), and the Base nonce. This is a specific verb-plus-resource statement. It does not, however, explicitly differentiate itself from near siblings like wallet, wallet_portfolio, check_counterparty, or sanctions_check, which leaves some routing ambiguity.

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?

It gives a concrete use case — 'Use to screen an address before paying it' — which is clear actionable context. It stops short of naming when-not-to-use or pointing at the alternative screening tools (check_counterparty, sanctions_check), so it is clear context without exclusions.

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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