Skip to main content
Glama

trade_finance_eligibility

Read-onlyIdempotent

Evaluates trade finance eligibility for CFOs by analyzing counterparty risk and jurisdiction using World Bank and BIS data. Inputs include counterparty country code (ISO 3166-1 alpha-3) and industry sector. Returns risk scores, eligibility flags, and financing terms. Ideal for assessing letters of credit, export credit agency guarantees, and other trade finance instruments. Keywords: trade finance, counterparty risk, jurisdiction risk, letters of credit, ECA guarantees.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
industrySectorYes
annualTradeVolumeUSDNo
counterpartyCountryCodeYes
counterpartyCreditRatingNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
eligibilityNo
financingTermsNo
countryRiskScoreNo
maxFinancingAmountUSDNo
recommendedInstrumentsNo

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the description does not need to repeat safety information. It adds useful context about data sources (World Bank, BIS) and output types (risk scores, eligibility flags, financing terms), going beyond the structured annotations without contradicting them.

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 concise and well-structured, with each sentence serving a purpose: purpose, inputs, outputs, and use cases. It is front-loaded with the main function and avoids redundancy or filler.

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?

The description provides sufficient context for an agent to select and invoke the tool: it explains what it does, who it's for, the key inputs, outputs, and typical use cases. Given the presence of an output schema, return values do not need exhaustive detail. However, it omits guidance on optional parameters and async behavior, which are partially covered by the 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 description coverage is low (20%). The description explains two required parameters (counterpartyCountryCode with ISO 3166-1 alpha-3 format, and industrySector) but omits the optional parameters (annualTradeVolumeUSD, counterpartyCreditRating, async). It partially compensates for the schema gap but not fully.

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's function: 'Evaluates trade finance eligibility for CFOs by analyzing counterparty risk and jurisdiction using World Bank and BIS data.' It uses a specific verb ('evaluates') and identifies the resource ('trade finance eligibility'), distinguishing it from siblings by focusing on eligibility assessment with counterparty and jurisdiction analysis.

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 provides clear use cases: 'Ideal for assessing letters of credit, export credit agency guarantees, and other trade finance instruments.' This gives context for when to use the tool, though it does not explicitly mention when not to use it or compare to alternative tools.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.