Authoritative rug/safety report for a Solana token (rugcheck.xyz): normalized risk score, whether mint & freeze authority are renounced, LP locked %, top-5 and top-10 holder concentration, named risk flags, and a plain verdict. Send { mint }. The safety gate before sniping any Solana token. [x402 paid tool — price $0.05; POST /api/sol/rug-check]
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | Solana token mint address |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool is paid ($0.05), uses a POST endpoint, and returns a structured report. It does not mention rate limits, error conditions, or what happens on invalid tokens, but the core behavior is well described.
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 four sentences, front-loading purpose and outputs. It includes pricing and endpoint info which are relevant. No redundancy; each sentence adds value. Slightly more concise than average but still effective.
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?
For a simple, single-parameter tool with no output schema and no annotations, the description explains purpose, inputs, and outputs reasonably well. However, it omits return format (JSON vs text) and error handling details, leaving some gaps 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?
Schema coverage is 100% with one parameter (mint). The description says 'Send { mint }' which adds no additional semantics beyond the schema's description. The listed output fields give context, but no deeper validation or format hints are provided. Baseline 3 is appropriate.
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 description clearly states the tool returns an authoritative rug/safety report for a Solana token, listing specific outputs (risk score, renounce status, LP lock, holder concentration, risk flags, verdict). It also mentions the source (rugcheck.xyz) and positions it as the safety gate before sniping, distinguishing it from sibling tools.
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 phrase 'The safety gate before sniping any Solana token' strongly implies when to use the tool. However, it does not explicitly state when not to use it or mention alternatives like snipe_safety or snipe_honeypot among siblings. The guidelines are clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.
All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.
With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.
The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.