RLUSD Compliance Confidence Index (CCI): proprietary composite score from peg stability (40%), reserve ratio (35%), market depth (25%). Grade A-F. MiCA-relevant.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the composite formula weights (40%/35%/25%) and grade range (A-F), which adds useful behavioral transparency about how the score is derived. However, it does not mention data sources, update frequency, or any limitations of the proprietary score.
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 extremely concise: two sentences, no fluff. It front-loads the purpose and then details the composition and grade, with every sentence providing substantive information.
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 tool has no parameters and no output schema, the description adequately explains the purpose and output nature. It covers the composite score weights and grade. A minor gap is not explaining the exact return format (e.g., numeric score versus grade string), but for a no-parameter tool, the description is fairly 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 schema coverage is 100% (empty schema). With no params, the description is not required to explain parameter semantics. The description adds value by explaining what the score measures and how it's composed, which is more than baseline for a parameterless tool.
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 it computes a Compliance Confidence Index for RLUSD using a weighted composite score and grades A-F. It identifies a specific resource (RLUSD) and a specific output (composite score/grade), distinguishing it from sibling tools like xrpl_rlusd_integrity or xrpl_rlusd_anchor by its composite proprietary scoring nature.
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 the tool is used to obtain a compliance/confidence score relevant to MiCA, but it does not explicitly state when to use this over alternatives like xrpl_compliance_check or xrpl_rlusd_integrity. The MiCA-relevant note gives some context, but exclusions and alternatives are absent.
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.