XRPL Token Guard

Check an XRPL token's safety

check_token_safety

Read-onlyIdempotent

Checks an XRP Ledger token for fake look-alikes, issuer mint/freeze/clawback powers, transfer fees, thin liquidity, and whale concentration. Returns a risk verdict with exact ledger-backed reasons.

Instructions

Live safety check of an XRP Ledger token (issued currency). Detects fake look-alikes of famous tokens (e.g. a fake RLUSD), issuers that can still mint, freeze or claw back, global freezes, transfer fees, unverified domains, whale concentration, thin AMM liquidity and brand-new issuers. Returns a verdict (High risk / Caution / No red flags found / Not enough data), the reasons behind it with the exact ledger facts, and a one-sentence spoken summary.

Input Schema

Name	Required	Description	Default
`issuer`	Yes	The token issuer's XRPL address (starts with r).
`currency`	Yes	Token ticker as shown in wallets (e.g. RLUSD, SOLO) or its 40-character hex currency code.

Output Schema

Name	Required	Description
`facts`	Yes
`score`	Yes	0-100 mechanical score; not a safety probability. Clawback is a high-risk control-policy failure.
`token`	Yes
`reasons`	Yes	The top reasons behind the verdict, most important first.
`verdict`	Yes
`findings`	Yes
`checked_at`	Yes
`disclaimer`	Yes
`ledger_index`	Yes
`more_info_url`	Yes
`verdict_label`	Yes
`spoken_summary`	Yes	One or two sentences ready for text-to-speech.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description goes further by disclosing the detection surface (mint/freeze/clawback capability, global freezes, transfer fees, unverified domains, whale concentration, AMM liquidity, brand-new issuers). Some of this is return-shape information that the existing output schema may already carry, which keeps it from a 5.

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

Conciseness4/5

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

Front-loaded with purpose, then a dense but well-ordered enumeration of detections, then the return summary. Slightly long for two sentences, but every clause adds a distinct fact rather than filler.

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

Completeness5/5

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

For a complex analysis tool, the description names the input domain, the detection surface, and the verdict vocabulary an agent will see. With an output schema present and annotations covering safety traits, nothing essential to correct invocation is missing.

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?

Schema description coverage is 100% and both parameters are documented there (issuer format, currency ticker-or-hex). The description adds no parameter-level detail such as issuer/currency consistency or hex-encoding rules, so the baseline 3 applies.

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

Purpose4/5

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

Specific verb and resource: 'Live safety check of an XRP Ledger token (issued currency)', plus an enumerated list of what it detects (fake look-alikes, mint/freeze/clawback issuers, thin AMM liquidity). It does not name or contrast itself with the sibling is_it_the_real_token, which overlaps on the 'fake token' detection ground, so differentiation is left to inference.

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?

Usage is only implied by the phrase 'Live safety check' – an agent can infer this is a pre-trade/pre-interaction screening step. There is no explicit when-to-use, no when-not-to-use, and no routing to check_wallet_security or is_it_the_real_token despite clear topical overlap with the latter.

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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