Audits Base ERC-20 token contracts for honeypot risks, buy/sell transfer taxes, liquidity depth, and prompt injection traps in token metadata. Price: 0.010 USDC on Base or Solana.
| Name | Required | Description | Default |
|---|---|---|---|
| token_address | Yes | Base ERC-20 contract address |
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| safe | No | ||
| symbol | Yes | ||
| honeypot | No | ||
| buy_tax_bps | No | ||
| sell_tax_bps | No | ||
| token_address | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "buy_tax_bps": {
+ "type": "integer"
+ },
+ "honeypot": {
+ "type": "boolean"
+ },
+ "name": {
+ "type": "string"
+ },
+ "safe": {
+ "type": "boolean"
+ },
+ "sell_tax_bps": {
+ "type": "integer"
+ },
+ "symbol": {
+ "type": "string"
+ },
+ "token_address": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "token_address",
+ "symbol",
+ "name"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, non-destructive, openWorld), but the description adds the crucial non-annotation fact that this is a paid call costing 0.010 USDC, plus the fact that it inspects untrusted token metadata for prompt injection. It does not mention rate limits, failure modes, or what happens if the address is not a Base contract, which keeps it short of a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences, zero filler: the first front-loads the scope and checks, the second immediately flags cost and payment chains. Every clause carries information an agent needs before calling.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need no explanation, and the description discloses the paid nature and analytical scope. What remains missing is how this relates to the overlapping honeypot and contract-inspection siblings, which matters for a toolset this dense.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter, token_address, and schema coverage is 100% with a 'Base ERC-20 contract address' description. The tool description adds no meaning beyond that — no note on address format, checksum, or behavior for non-contract addresses — so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Audits') and resource ('Base ERC-20 token contracts') and enumerates the checks performed: honeypot risk, buy/sell taxes, liquidity depth, metadata prompt injection. This is far more specific than the sibling 'checkSmartContractHoneypot', but the description never names that sibling or explains how the two overlap, so discrimination requires inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied by the enumerated risk categories — an agent can infer this is for pre-trade token due diligence. There is no explicit when-to-use/when-not statement and no routing versus checkSmartContractHoneypot, inspectContractInfo, or runFullEnterpriseRiskAudit, which appear to overlap.
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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