DPX — Institutional Cross-Border Settlement

market.cascade

Read-onlyIdempotent

Butterfly Effect Cascade Intelligence — models how a shock in one macro domain propagates through the interconnected web of climate, geopolitical, economic, and commodity systems. Given an origin event (e.g. armed conflict escalation, agricultural drought, central bank rate decision, rare earth export restriction) and a magnitude score, returns a time-ordered cascade chain showing which downstream systems are hit, in what sequence, with what attenuated signal strength, and an AI synthesis briefing on the highest-impact transmission paths. Covers 24 nodes across 4 domains: climate (drought, flood, carbon price, wildfire, sea-level stress, heatwave), geopolitical (sanctions, conflict, trade tariffs, regime change, election shock, port blockade), economic (rate decisions, inflation, sovereign debt, banking stress, currency crisis, recession), and commodity (oil, gas, grain, rare earth/lithium, copper, water, fertilizer). Purely macro intelligence — no settlement or stablecoin mechanics.

Input Schema

TableJSON Schema

Name	Required	Description
`origin`	No	Origin node ID. Call market.cascade with listNodes:true to discover valid IDs (e.g. "geo.conflict", "climate.drought", "commodity.oil", "macro.rate_decision").
`eventType`	No	Free-text description of the specific event (e.g. "Russia-Ukraine escalation", "Sahel drought season", "Fed emergency 75bps hike").
`listNodes`	No	If true, returns all valid origin node IDs and descriptions instead of running a cascade. Use this first to discover valid origin values.
`magnitude`	No	Shock magnitude 1–100. 100 = maximum plausible shock for this event type. 40–60 = significant but not extreme.
`horizonHours`	No	Forward time horizon in hours (1–720). Default: 168 (1 week). Use 24 for immediate cascade, 720 for full 30-day view.

Output Schema

TableJSON Schema

Name	Required	Description
`origin`	No	Origin node metadata.
`cascade`	No	Time-ordered propagation chain — each entry has node, magnitude, arrivalHours, via path, and mechanism.
`eventType`	No	Event description provided.
`synthesis`	No	AI intelligence briefing on transmission paths, concentrated risk, feedback loops, and forward signals.
`computedAt`	No	ISO timestamp of computation.
`horizonHours`	No	Time horizon modeled.
`inputMagnitude`	No	Clamped input magnitude.

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable context: the output is a time-ordered cascade chain with attenuated signal strength and an AI synthesis briefing. It also clarifies that the tool is purely macro intelligence with no settlement or stablecoin mechanics. This goes beyond the annotations and provides behavioral transparency about the type of output and scope.

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 well-structured and efficient. The first sentence establishes the core purpose, the second sentence lists the inputs and outputs, the third sentence enumerates the 24 nodes across 4 domains, and the final sentence clarifies scope. Every sentence is necessary and contributes to understanding. It is front-loaded with the most important information.

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 tool's complexity (5 parameters, output schema exists), the description is quite complete. It explains how to use listNodes, what the output includes, and what domains are covered. It also explicitly states what it does not cover (settlement/stablecoin). The only minor gap is that it does not describe the output format in detail, but since an output schema is provided, that is acceptable.

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 description coverage is 100%, so the schema already documents each parameter. The description adds extra value: it explains the purpose of listNodes (discover valid IDs), gives concrete examples for eventType, defines magnitude scale with examples (100 = maximum plausible shock), and suggests horizonHours values (24 for immediate, 720 for 30-day). This enriches the parameter semantics beyond the schema.

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 verb ('models how a shock propagates') and resource ('macro domains across climate, geopolitical, economic, and commodity systems'). It lists specific node examples and explicitly distinguishes itself from settlement/stablecoin tools, which is a strong differentiator from siblings like intelligence.contagion or forecast.scenario.

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 explains how to use the tool: call with listNodes first, then provide origin, eventType, magnitude, horizonHours. It also gives example values for magnitude and horizonHours. However, it does not mention when to use this tool versus alternatives (e.g., intelligence.aftershock or intelligence.tectonic), nor does it state when not to use it. The usage guidance is adequate but not explicit about exclusions.

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

A4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, especially within their domains (e.g., analytics, compliance, ESG, forecasting). However, a few tools like route and stability.stablecoin_route or settlement.quote and fx.cost_certainty may cause confusion despite distinct descriptions, and the large number of intelligence tools (cascade, aftershock, contagion, etc.) could lead to misselection without careful reading.

Naming Consistency3/5

Naming follows a domain prefix pattern (e.g., agent.kya_register, settlement.quote, esg.score), which provides some structure. However, inconsistencies exist: some tools use underscores (batch_settle, flow_check), others are single words (route), and the mix of verb_noun and noun_verb styles (e.g., compliance.pep_screen vs market.fx) reduces predictability.

Tool Count3/5

At 71 tools, the server is very broad in scope, covering compliance, ESG, forecasting, intelligence, treasury management, and more. While each tool seems justified for the complex institutional domain, the sheer number may overwhelm agents and makes the set feel bloated. A more focused scope or tighter tool grouping would improve appropriateness.

Completeness4/5

The tool surface is remarkably comprehensive for cross-border settlement, covering end-to-end workflow from quoting, FX analysis, compliance screening, ESG scoring, forecasting, and multiple payment rails (Mercury, Ramp, SWIFT). Minor gaps exist (e.g., no tool to update a settlement after execution), but core operations are well-covered, and the addition of integration and audit trails enhances completeness.

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