DPX — Institutional Cross-Border Settlement

esg.batch

Read-only

Screen up to 50 entities in a single call. Accepts LEIs or company names (GLEIF-resolved). Returns results ranked by composite ESG score descending — highest scoring counterparties first. Useful for portfolio-level compliance screening, supplier due diligence, and TMS pre-payment checks. Name resolution is slower than direct LEI input.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`leis`	No	Array of LEIs to screen (fastest path — no GLEIF resolution needed).
`names`	No	Array of company names to screen (resolved via GLEIF — slower, allows ≤3s per name).

Output Schema

TableJSON Schema

Name	Required	Description
`total`	No
`failed`	No
`results`	No	Entities sorted by composite score descending. Each item includes lei, entityName, score object, or an error note.
`succeeded`	No

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, making safety profile clear. Description adds valuable behavioral details: batch size ceiling of 50, GLEIF resolution for names, ranking by composite ESG score, and a latency nuance for name-based queries. No contradictions with annotations.

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?

Four sentences, each earning its place: capacity & input types, output behavior, use cases, performance caveat. Front-loaded with the core action. No redundancy or fluff.

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?

Given that input schema and output schema exist (schema coverage 100%, output schema present), the description fully completes the picture by covering capacity, input options, ranking behavior, use cases, and performance nuance. No gaps remaining.

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 baseline is 3. The description adds value by clarifying that LEIs are the 'fastest path' and that names go through slower GLEIF resolution ('≤3s per name'), enhancing parameter understanding beyond schema alone.

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?

Clearly states a specific verb ('Screen') and resource ('entities'), specifies batch size limit (50), input types (LEIs or company names), and output behavior (ranked by ESG score descending). Distinguishes from siblings like esg.lookup by focusing on batch screening vs single entity.

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?

Explicitly lists use cases: 'portfolio-level compliance screening, supplier due diligence, and TMS pre-payment checks'. Notes performance trade-off ('Name resolution is slower than direct LEI input'). Lacks explicit when-not-to-use or alternative tool names, though some are implicitly evident from sibling context.

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

All DPX — Institutional Cross-Border Settlement tools Inspect

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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.

Resources

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