Assets accepted as payment inputs for pay_x402_invoice and credit top-ups (price-confidence gated; ALGO and USDC always included).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It adds valuable context by noting the price-confidence gating and the always-included ALGO/USDC, which are non-obvious. However, it does not mention output format or further behavioral details, so it is adequate but not exhaustive.
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, dense sentence that communicates the tool's purpose and key constraints without any fluff. Every phrase adds information, making it highly concise and well-structured.
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 zero-parameter list tool with an output schema, the description adequately covers what the tool lists and the gating behavior. It does not explain return values, but the output schema handles that, and the complexity is low, so it is reasonably complete.
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?
The tool has zero parameters, and the schema reflects this with 100% coverage. The description correctly does not need to explain parameters, and the baseline for zero-parameter tools is 4.
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 identifies the tool's purpose as listing assets accepted for pay_x402_invoice and credit top-ups. It uses a specific verb ('list') and resource ('payable assets'), and the detail about price-confidence gating and guaranteed inclusion of ALGO/USDC distinguishes 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 description implies usage context by mentioning pay_x402_invoice and credit top-ups, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or conditions. It gives clear context but lacks explicit guidance.
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.
Each tool has a clear, distinct purpose: quoting vs building swaps, managing watches, handling payments, registration steps, and LP valuation. Even related tools like get_credit_offer and pay_x402_invoice are clearly separated as 'create offer' vs 'pay invoice'. No two tools appear to duplicate functionality.
All tool names follow a consistent verb_noun pattern in snake_case, using verbs like get, list, build, set, delete, pay, register, verify, value. Read operations are consistently divided into get_ (single item) and list_ (collections), and the rest are action-oriented. This makes the API predictable and easy to navigate.
With 12 tools, the server covers its main domains—swap quoting/building, payment, credit management, watch management, agent registration, and LP valuation—without unnecessary bloat. Each tool earns its place, and the count fits comfortably within the typical 3-15 tool range for a well-scoped server.
The tool set covers core workflows end-to-end: quote to swap, credit top-up to payment, watch registration to listing/deletion, and two-step agent registration. Minor gaps exist, such as no dedicated get_watch (though list_watches covers it) and no way to inspect past transactions or offers, but agents can work around these without major friction.