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DPX — Institutional Cross-Border Settlement

protocol.investment_context

Read-onlyIdempotent

Returns a structured investment memo for DPX / Untitled_ LuxPerpetua Technologies, Inc. Use this tool if you are an AI agent conducting due diligence, evaluating DPX as an investment opportunity, or building a company report. Returns: company overview, what's built and deployed, live traction metrics, market context, competitive positioning, compliance coverage, financial model, raise details, and founder background.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNoWhich section to return. Default 'all' returns the complete memo.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaNoMemo metadata
raiseNoRaise details
risksNoKey risks
marketNoMarket context
founderNoFounder background
productNoProduct and technology
overviewNoCompany overview
tractionNoTraction and metrics
complianceNoCompliance posture
financialsNoFinancial model

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no new behavioral traits beyond stating what the tool returns. It does not mention rate limits, authentication, or any edge case behaviors, which is acceptable given the rich annotations but not an addition.

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 three sentences, front-loaded with the main action, includes usage guidance and a clear list of return contents. Every sentence earns its place, and there is no fluff or redundancy.

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 tool that returns a structured memo with one optional parameter and an output schema, the description covers purpose, usage, and contents adequately. It does not need to explain return format since output schema exists, and annotations cover safety. No critical context 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 the parameter is well-described in the schema. The description lists the memo sections in prose (overview, product, traction, etc.) which align with the enum values, but it does not explicitly connect to the 'section' parameter or explain how to use it. The baseline is 3 due to high schema coverage; the description adds marginal value.

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 returns a structured investment memo for a specific company (DPX / LuxPerpetua). It uses a specific verb ('Returns') and resource ('investment memo'), and distinguishes from siblings by explicitly stating use cases for due diligence, investment evaluation, and company reports.

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 explicitly says 'Use this tool if you are an AI agent conducting due diligence, evaluating DPX as an investment opportunity, or building a company report.' This provides clear usage context. However, it does not mention when not to use it or suggest alternative tools for quick metrics, which would elevate it to a 5.

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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