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XRPL-Utilities

@xrpl-utilities/mcp

xrpl_pulse_token_health

Evaluate XRPL token health with 0-10 scores for sovereignty, distribution, liquidity, transparency, and demand pipeline. Filter by issuer wallet or currency code.

Instructions

Free. Per-token health scores for top 200 XRPL tokens: sovereignty, distribution, liquidity, transparency, demand pipeline. Each dimension 0-10 with green/yellow/red. Filter by issuer wallet or currency code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoCurrency code (e.g. SOLO, RLUSD). May return multiple issuers.
sortNoSort field: total, sovereignty, distribution, liquidity, transparency, demand_pipeline, marketcap, holders.total
limitNoMax results (1-200).
issuerNoXRPL issuer wallet address (r-address). Returns single token.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that the tool is free, limited to top 200 tokens, and returns scores per dimension with a 0-10 scale and color coding. This gives a clear picture of output and cost, though it does not mention rate limits or authentication requirements, which are not critical for a read-only analytics tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with 'Free.' and clearly structured. It efficiently conveys the core value, scope, output format, and filtering options without any redundant or verbose language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description explains the return style (0-10 scores with green/yellow/red) and the token scope (top 200). It also mentions filtering, which together covers the essential context for a user to understand what this tool returns. Minor details like the exact response structure or sort behavior are left to the schema, but the description is sufficient for initial understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers all four parameters with detailed descriptions, achieving 100% coverage. The description merely restates the filtering options (issuer wallet or currency code) without adding new semantic details beyond what the schema provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies a unique purpose: providing per-token health scores for XRPL tokens across five named dimensions. It distinguishes itself from sibling tools by focusing on health scores rather than events, flows, or trust domains, and the verb 'health scores' is specific and informative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for token health assessment, noting the coverage of top 200 tokens and the ability to filter by issuer or currency. However, it does not explicitly state when to use this tool over alternatives or provide exclusions, leaving usage guidance mostly inferred from the scope and sibling names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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