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DPX — Institutional Cross-Border Settlement

esg.lookup

Read-onlyIdempotent

Resolve a company name, domain, or ticker to a LEI via GLEIF and return the full ESG score. Removes the need for callers to have a LEI. Returns Environmental (40%), Social (35%), and Governance (25%) pillar scores, composite 0–100, fee surcharge tier, and per-source breakdown (SEC EDGAR, OSHA, BLS SOII, EU E-PRTR, ESMA, World Bank WGI, GLEIF). Use when you have a company name but not a LEI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesCompany name, domain, or ticker to look up (e.g. "Apple Inc", "siemens.com", "MSFT")
countryNoISO-2 country code to narrow results (e.g. "US", "DE"). Optional but improves match accuracy.
narrateNoSet true to include a 2–3 sentence plain-English compliance narrative generated by the AI synthesis layer.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundNo
scoreNoFull ESG score object with composite, environmental, social, governance, feeTier, feeSurcharge, sources, coverage
resolvedNo
narrationNoPlain-language compliance narrative (only when narrate=true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds significant context: it uses GLEIF for resolution, returns specific pillar scores, a composite, fee surcharge tier, and a per-source breakdown. It also mentions the AI synthesis layer for the narrate parameter. 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.

Conciseness4/5

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

The description is a single paragraph of four sentences, front-loading the main action. It is concise with no fluff, though it could be more structured (e.g., bullet points) for readability. Every sentence serves a purpose.

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 has 3 parameters (all described), an output schema, and annotations covering safety, the description adequately explains the output structure and usage context. It covers the main purpose, input types, and output components. Minor gaps: the fee surcharge tier and sources are mentioned but not detailed, likely covered by output schema.

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 coverage is 100%, so the baseline is 3. The description adds some context (e.g., resolution via GLEIF, removal of LEI requirement) but does not elaborate on parameter syntax or format beyond what the schema provides. It meets the baseline but does not exceed it significantly.

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 resolves a company name/domain/ticker to a LEI and returns full ESG scores. It distinguishes from siblings like esg.score by explicitly stating it removes the need for a LEI, and provides a specific use case ('Use when you have a company name but not a LEI').

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 gives explicit when-to-use guidance ('Use when you have a company name but not a LEI'). It implies when not to use (if you have a LEI, use another tool) but does not explicitly name alternatives. The return structure is described, aiding tool selection.

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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