xrpl_account_intel
XRPL account intelligence: XRP balance, trust lines, open offers, escrows, flags
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | XRPL classic address (r...) |
XRPL account intelligence: XRP balance, trust lines, open offers, escrows, flags
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | XRPL classic address (r...) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the scope of data returned (balance, trust lines, offers, escrows, flags), which implies a read-only lookup. However, it does not mention whether it queries the live ledger, if the address must exist, or any error/edge-case behavior, leaving gaps in transparency.
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, compact sentence with no unnecessary words. The colon-separated list is efficient and instantly scannable, making it easy for an agent to parse the tool's purpose.
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 one-parameter read operation, the description covers the key data categories, but it does not address potential return formats, pagination, or error conditions. Since there is no output schema, the description itself needs to provide enough context for the agent to know what to expect; it is adequate but not fully 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 input schema fully describes the single parameter 'address' with 'XRPL classic address (r...)', achieving 100% coverage. The description adds no additional parameter semantics, so it meets the baseline where the schema does the heavy lifting.
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 enumerates the specific account data included (XRP balance, trust lines, open offers, escrows, flags), which distinguishes it from sibling tools that target individual aspects. However, it lacks a strong imperative verb like 'get' or 'retrieve', using the nominal 'intelligence' instead, which leaves the action implied rather than 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?
No guidance is given for when to use this tool versus siblings like xrpl_trust_lines or xrpl_escrow_check. The description implies it provides an aggregate account snapshot, but it does not explicitly state that it should be preferred for a high-level overview or when multiple data types are needed at once, nor does it mention alternatives.
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.