xrpl_rlusd
RLUSD stablecoin compliance and risk intelligence: peg health, supply, NYDFS compliance
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
RLUSD stablecoin compliance and risk intelligence: peg health, supply, NYDFS compliance
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for disclosing behavior. It only lists topics and does not indicate whether the tool is read-only, what data it accesses, whether it returns a score, or any side effects. This is a significant gap for a tool with zero annotation support.
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 very short, but it is a sentence fragment rather than a complete, well-structured description. It is not verbose, but it lacks a clear subject-verb structure and feels like a label rather than a functional explanation.
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?
Given the absence of output schema and annotations, the description should provide more context about what the tool returns or how to interpret its results. It only lists topic areas, leaving the agent without enough information to understand the tool's functionality or output. The low complexity (0 params) slightly reduces the need, but the vagueness still makes it incomplete.
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, so the schema provides no parameter details. The description indirectly clarifies the tool's subject matter (RLUSD compliance data), which is the only relevant semantic context. This aligns with the baseline of 4 for tools with no parameters.
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 states the tool is about 'RLUSD stablecoin compliance and risk intelligence' and lists specific focus areas (peg health, supply, NYDFS compliance). However, it lacks a clear action verb such as 'retrieve' or 'analyze', making it a noun phrase rather than a specific operation. It does provide some differentiation from siblings like xrpl_rlusd_supply, but the purpose remains vague.
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 gives no guidance on when to use this tool versus alternatives. It does not mention any specific scenarios, exclusions, or alternative tools, leaving the agent without direction for tool selection.
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.
Several tools have overlapping purposes, particularly the escrow check/monitor pair and the many RLUSD tools covering supply, integrity, holders, and compliance. Account-related tools like account_intel, gateway_balances, and token_check also share boundaries. An agent would need careful reading to choose correctly.
All tools share the xrpl_ prefix and use snake_case consistently. However, the second part mixes nouns and verbs (e.g., overview, iso20022, path_find, quantum_join), so the pattern is not strictly verb_noun. This is still readable and predictable.
31 tools is on the heavy side for an oracle server, especially with 9 RLUSD-specific tools that could be consolidated. The breadth of XRPL topics is large, but the count feels inflated beyond what an agent needs.
The tool set covers the major XRPL domains: accounts, DEX, AMM, NFTs, escrow, payments, compliance, and RLUSD. There are no glaring dead ends for an oracle use case. Some areas like transaction history are missing, but they fall outside the intelligence scope.