Convert an amount between any two crypto/fiat assets at live rates. Send { amount, from, to }, e.g. convert 1.5 ETH to USDC. Instant FX for agents pricing on-chain actions. [x402 paid tool — price $0.003; POST /api/crypto/convert]
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target ticker, e.g. USDC | |
| from | Yes | Source ticker, e.g. ETH | |
| amount | Yes | Amount of the 'from' asset |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It mentions 'live rates' and 'Instant FX' but doesn't disclose whether it's a read operation, potential errors, or rate limits. It implies a POST request but doesn't confirm no side effects. Adequate but not thorough.
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?
Extremely concise: two sentences plus a line with price and endpoint. Purpose is front-loaded, no wasted words. Every sentence adds value.
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?
Simple tool with 3 required parameters and no output schema. Description covers the core behavior, use case, and pricing. Could mention return format or error handling, but for a conversion tool this is sufficient. Not complete enough for a complex tool but good here.
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 descriptions, so baseline is 3. Description adds value by providing an example ('e.g. convert 1.5 ETH to USDC') and explicitly listing the structure '{ amount, from, to }', reinforcing schema meaning.
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?
Description clearly states it converts between crypto/fiat assets at live rates, with a specific example (1.5 ETH to USDC). The verb 'convert' and resources are explicit, and it distinguishes from siblings like crypto_price by focusing on conversions.
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?
Provides a clear use case ('Instant FX for agents pricing on-chain actions') and notes it's a paid tool with price. Lacks explicit when-not-to-use or alternatives, but the example and context make usage clear.
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.