xrpl_trust_lines
XRPL trust line analysis: all issued currencies an account holds. Shows balances, issuers, compliance status.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| account | Yes | XRPL account to analyze |
XRPL trust line analysis: all issued currencies an account holds. Shows balances, issuers, compliance status.
| Name | Required | Description | Default |
|---|---|---|---|
| account | Yes | XRPL account to analyze |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations to fall back on, so the description carries the full burden. It only mentions the output ('Shows balances, issuers, compliance status'), but does not disclose behavioral traits such as whether it performs a read-only query, any rate limits, or how compliance status is derived. This is a gap for an analysis tool.
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, well-structured sentence that packs in the resource, scope, and output summary. Every word earns its place, with no redundancy or filler.
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 tool with one parameter and no output schema, the description covers the core: what it analyzes (trust lines), the scope (all issued currencies), and what it returns (balances, issuers, compliance status). It could optionally mention that it reads live ledger data or how to interpret compliance status, but it is adequate for basic selection and invocation.
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 input schema has one parameter 'account' with a generic description, but the tool description adds the meaning that the account is the holder of the trust lines ('an account holds'). This enriches the parameter semantics beyond the schema, even though schema coverage is 100%.
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 the tool performs trust line analysis on XRPL, specifically listing 'all issued currencies an account holds'. It distinguishes from siblings like xrpl_gateway_balances by focusing on the account's trust lines, not gateway balances. The verb 'analysis' and resource 'trust lines' are explicit.
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 when wanting a comprehensive view of an account's issued currencies, but it does not provide explicit when-to-use guidance or exclude alternatives. It does not mention any related tools like xrpl_token_check or xrpl_compliance_check, leaving the agent to infer appropriate use from context.
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.