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Token rug check (Solana / Robinhood Chain)

token_rugcheck

Verify a token's safety before trading. Receive a GO/CAUTION/DANGER verdict by analyzing mint/freeze authorities, holder concentration, and scam flags on Solana or Robinhood Chain.

Instructions

Safety check a token BEFORE buying or swapping. Returns GO/CAUTION/DANGER. Solana: freeze/mint authority, transfer controls, holder concentration. Robinhood Chain: holder concentration, burned %, scam flags. Use for any unfamiliar token.

PAID TOOL: up to $0.02 USDC.e per call (MPP on Tempo). Paid automatically from your configured wallet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainYesChain: solana or rhchain.
tokenYesSolana mint (base58) or Robinhood Chain contract address (0x...).
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses the return categories, the chain-specific checks performed, and the automatic payment mechanism with cost. This goes beyond a simple 'safety check' by exposing what checks happen and that it is a paid operation. It does not detail failure modes or data sources, but the essential behavior is clearly communicated.

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?

The description is two concise paragraphs. The first sentence states the main action and output, the next sentences list key checks, and the final paragraph covers cost. Every sentence adds value, and the structure is front-loaded with the most critical usage guidance.

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?

Given no output schema, the description adequately explains the outcome (GO/CAUTION/DANGER) and includes chain-specific criteria. It covers both supported chains and payment context, making it reasonably complete for a two-parameter tool. Some detail on the response format beyond the label would improve completeness, but it is not a major gap.

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%, with both parameters fully described in JSON Schema. The description does not add much beyond the schema, though it reinforces the meaning of 'token' by showing chain-specific address formats. Baseline 3 is appropriate because the schema already documents parameters adequately.

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?

Description uses a specific verb ('Safety check') and clearly identifies the resource ('a token') and scope ('Solana / Robinhood Chain'). It explicitly states the output is a GO/CAUTION/DANGER rating, which distinguishes this safety tool from sibling price, supply, or yield tools. The phrase 'Use for any unfamiliar token' reinforces its distinct purpose.

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?

Description provides clear when-to-use guidance: 'BEFORE buying or swapping' and 'Use for any unfamiliar token.' It does not explicitly name alternative sibling tools or explain when not to use, but the context is unambiguous enough for selection decisions. The paid-tool warning also helps the agent know cost implications.

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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