Exact calculator + unit conversion (arbitrary precision). e.g. '3 inch to cm', 'sqrt(2)^10'. Send { expression, precision? }. [x402 paid tool — price $0.003; POST /api/calc]
| Name | Required | Description | Default |
|---|---|---|---|
| precision | No | Decimal places 0-64 | |
| expression | Yes | Math expression, optionally with units |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the tool as an 'exact calculator' with arbitrary precision and mentions pricing and endpoint. However, it does not disclose behaviors such as error handling, rate limits, or the format of results, which are important for an agent to use it correctly.
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 a single sentence that efficiently conveys the core functionality, provides examples, and includes essential meta-information (pricing, endpoint). Every part serves a purpose with no redundancy.
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 calculator tool with well-documented parameters and no output schema, the description covers the primary functionality, examples, and pricing. It could additionally explain return format or error cases, but is sufficiently complete for an agent to invoke the tool.
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 for both parameters. The description adds value by providing usage examples ('3 inch to cm', 'sqrt(2)^10') that illustrate how parameters can be used together, and it indicates that 'precision' is optional with a question mark, going beyond the schema.
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 'Exact calculator + unit conversion (arbitrary precision)' and provides concrete examples like '3 inch to cm' and 'sqrt(2)^10', making the tool's purpose unmistakable. Sibling tools are analytical or data retrieval tools; this is the only calculator, so it is well-differentiated.
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 implies usage for mathematical and unit conversion tasks through examples but does not explicitly state when to use this tool versus alternatives, nor does it provide guidance on when not to use it.
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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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.