cerberus-index

watch_token

Monitor an XRPL token you hold and get alerted when it turns dangerous. A one-time check can't catch a rug that happens later — this watches the chain continuously for: AMM pool destroyed (completed rug), liquidity drained past your threshold, clawback enabled, global freeze set, issuer un-blackholed (supply re-mintable), issuer blocklisted, LP lock weakened. Returns a subscriber_key — STORE IT — then poll check_alerts (free). Registration is refused (with the reason) for tokens that are ALREADY compromised — blocklisted, clawback-enabled, frozen, or a husk pool — since those need a verdict now, not monitoring later. Sold as packages by monitoring window (duration_days): 1d $0.005 · 3d $0.012 · 7d $0.020 · 14d $0.035 · 21d $0.048 · 30d $0.060 USDC (longer = cheaper per day). The x402 payment demand lists every tier; pay the one you want and the watch length is set by what you pay. Calling again renews (extends) the watch. Missing something? Call submit_feedback (free) to request it.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`issuer`	Yes
`currency`	Yes
`rebaseline`	No
`duration_days`	No
`subscriber_key`	No
`drain_threshold_pct`	No

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description discloses many behaviors: monitored conditions, refusal for already compromised tokens, pricing packages, renewal on calling again, and return of subscriber_key. It is mostly transparent but could clarify the x402 payment flow and that the tool costs money.

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?

The description is somewhat long but every sentence adds value. It is front-loaded with the main purpose and then details. Minor redundancy could be trimmed, but overall well-structured.

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 6 parameters, no output schema, and no annotations, the description covers the tool's behavior, return value, pricing, limitations, and lifecycle (e.g., renewal). It mentions related tools. It is fairly complete, though the rebaseline parameter is unaddressed and the payment mechanism could be clearer.

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

Parameters4/5

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

Schema coverage is 0%, so description must add meaning. It explains issuer, currency, duration_days (via package listing), drain_threshold_pct (via 'liquidity drained past your threshold'), and subscriber_key (used for renewal). However, the 'rebaseline' parameter is not mentioned, leaving a gap.

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 states the tool monitors an XRPL token continuously for dangerous conditions, listing specific events. It differentiates from sibling tools like check_xrpl_token which does a one-time check, and mentions alternative tools like check_alerts and submit_feedback.

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

Usage Guidelines4/5

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

The description explains when to use (holding a token needing continuous monitoring), when registration is refused (already compromised tokens), and what to do after (store subscriber_key, poll check_alerts). It could be more explicit about when to use sibling tools like check_xrpl_token as an alternative.

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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TDQS

A3.7/5.0

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count4/5

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.

Completeness5/5

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.

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