xrpl_amm_pools
XRPL AMM liquidity pool intelligence: reserves, trading fee, LP token supply
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| asset | No | RLUSD | |
| asset2 | No | XRP |
XRPL AMM liquidity pool intelligence: reserves, trading fee, LP token supply
| Name | Required | Description | Default |
|---|---|---|---|
| asset | No | RLUSD | |
| asset2 | No | XRP |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates the tool supplies pool data, implying a read-only operation, but it does not disclose side effects, permissions, rate limits, or any other behavioral traits. There is no contradiction with annotations, but the description falls short of meaningful 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 sentence with no filler, immediately stating the domain and key data points. It is appropriately brief and front-loaded, earning a perfect score for conciseness.
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 that there is no output schema and no annotations, the description should clarify what the response contains and how the optional parameters influence the query. It fails to explain the output structure beyond vague terms like 'intelligence', and it does not connect the parameters to the data returned, leaving the tool under-specified.
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 includes two parameters (asset and asset2) with no descriptions, and the tool description does not explain their role or how they affect the query. Since schema description coverage is 0%, the description should compensate, but it merely lists outputs and leaves the parameters ambiguous.
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 as providing XRPL AMM liquidity pool data, specifying key outputs such as reserves, trading fee, and LP token supply. However, it lacks a definitive action verb and doesn't explicitly differentiate from sibling tools like xrpl_dex_orderbook or xrpl_trust_lines.
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 provides no guidance on when to use this tool versus alternatives, and it does not mention any prerequisites or exclusion criteria. The only implicit usage is derived from the domain name 'AMM pools' in the title, which is not sufficient 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.