honeypot_check
Fast honeypot check. Args: address (0x...), chain. Returns: honeypot boolean, canBuy, canSell, buyTax, sellTax, riskScore.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chain | Yes | Chain name | |
| address | Yes | Token contract address |
Fast honeypot check. Args: address (0x...), chain. Returns: honeypot boolean, canBuy, canSell, buyTax, sellTax, riskScore.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | Yes | Chain name | |
| address | Yes | Token contract address |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry behavioral transparency. It does enumerate the returned fields (honeypot boolean, canBuy, canSell, buyTax, sellTax, riskScore), which gives some insight into what the tool reports. However, it does not state whether the operation is read-only, whether it performs on-chain calls, or whether any side effects or external dependencies exist.
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?
The description is extremely concise and free of unnecessary words, directly stating purpose, arguments, and return fields in a compact format.
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?
Because there is no output schema, listing return fields is helpful and partially compensates for missing output types. However, the description lacks explicit data types (e.g., whether canBuy/canSell are booleans), error behavior, and examples for the chain parameter, leaving some ambiguity for an agent.
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?
All two parameters are described in the schema, and the description adds useful detail by specifying '0x...' for the address and clarifying it as a token contract address. The 'chain' parameter remains generic ('Chain name'), but the overall parameter meaning is clear for typical use.
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?
The phrase 'Fast honeypot check' clearly identifies the tool's purpose as evaluating whether a token is a honeypot, and the listed return fields reinforce that intent. However, it lacks an explicit verb and does not directly contrast with the sibling 'scan_token' tool.
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?
The description provides no guidance on when to choose this tool over the sibling scan_token, nor does it mention any context such as speed trade-offs or suitability. The word 'Fast' hints at performance, but this is not developed into actionable selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.