Recently detected XRPL AMM pools (newest first, max 100), enriched: readable name, age, initial liquidity and fee, plus an honest launch-time screening label. Price: $0.010 USDC. Missing something? Call submit_feedback (free) to request it.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It does disclose pricing ($0.010 USDC), result size limits ('max 100'), sorting ('newest first'), and enrichment fields. However, it does not explain the nature of the 'honest launch-time screening label,' potential errors, or whether results are cached/snapshot-based. Some key behaviors remain opaque.
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 two concise sentences, front-loaded with the core purpose and key data attributes. Every sentence earns its place: the first covers purpose, ordering, limit, and richness; the second covers pricing and feedback path. No wasted words.
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's simplicity (one optional parameter, no output schema), the description provides a solid overview of returned content, ordering, and constraints. It mentions a price and a fallback feedback mechanism. It is not fully exhaustive (e.g., no explicit field types or example response), but adequate for a list-retrieval tool without an output schema.
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 a single 'limit' integer with a default of 20 and 0% description coverage. The description does not explain this parameter at all, only mentions a global 'max 100' cap. The parameter name and default hint at meaning, but the description adds no semantic value beyond the schema itself.
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 returning 'Recently detected XRPL AMM pools' with specific enrichment details (readable name, age, initial liquidity, fee, screening label). It includes ordering ('newest first') and a limit ('max 100'), giving concrete scope. It does not explicitly contrast with sibling tools, but the resource and action are unambiguous.
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?
Usage context is implied: use this when you want newly detected XRPL AMM pools, with a clear ordering and maximum. However, there are no explicit when-to-use or when-not-to-use instructions, nor alternatives mentioned aside from a generic 'submit_feedback' call. The guidance is adequate but not explicit.
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.
Each tool targets a distinct resource and action: address checks, token checks, price analysis, transaction simulation, path finding, wallet history, pool discovery, attestation, and monitoring all have clear boundaries. While some tools share domain (e.g., check_xrpl_token vs resolve_asset), their purposes are clearly differentiated in descriptions.
Nearly all tools follow a verb_noun pattern (check_*, get_*, verify_*, analyze_*, explore_*, find_*, quote_*, watch_*, submit_*). The only slight deviation is 'token_holders', a noun phrase, but it is still concise and follows the same lowercase snake_case style, so it does not create confusion.
20 tools is on the heavier side of the ideal range, but the server's scope—cross-chain security, token analysis, monitoring, attestation, and market data—justifies this breadth. Each tool covers a distinct sub-domain, so the count is reasonable though slightly above the typical 3-15 sweet spot.
The tool surface comprehensively covers the domain: token discovery, safety, identity, price, holders, monitoring, address/issuer risk, transaction simulation, route finding, wallet activity, endpoint trust, and attestation. There are no obvious dead ends; users can discover tokens, verify them, track them, and receive alerts—a full lifecycle for crypto risk assessment.
