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africa_trade_finance_esg_rater

Read-onlyIdempotent

As a COO, evaluate ESG compliance of African trade finance providers using World Bank WITS trade statistics and CDP climate disclosure data. Input the financial institution's name or identifier, and receive an ESG rating with breakdown across environmental, social, and governance dimensions. Ideal for due diligence on trade partners or portfolio risk assessment. Pass async:true to avoid timeout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoAssessment year (2018-2023)
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.
countryCodeNoISO 2-letter country code (e.g., 'ZA' for South Africa)
institutionNameYesFull name of the trade finance provider (e.g., 'Standard Bank Group')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesYes
warningsYes
esgRatingYes
socialScoreNo
tradeVolumeNoAnnual trade finance volume (USD)
carbonIntensityNoCO2 emissions per million USD financed (tons)
governanceScoreNo
environmentalScoreNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description adds complementary context by mentioning data sources (WITS, CDP) and the output breakdown. The async:true guidance to avoid timeout is a valuable behavioral detail not present in annotations. No contradictions found.

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 concise at three sentences, covering purpose, input, use case, and async tip without redundancy. The opening 'As a COO' is minor but not distracting, and the structure is front-loaded with the core function.

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?

For a read-only rater with an output schema and rich annotations, the description covers the essential aspects: data sources, output dimensions, use cases, and performance guidance. It doesn't explicitly state the geographic scope boundary, but that is implied by the tool name and target audience.

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 coverage is 100%, so the baseline is 3. The description adds practical meaning for institutionName ('name or identifier') and explains async's purpose ('avoid timeout'), going slightly beyond the schema. Year and countryCode are clear from the schema alone, so the description doesn't need to repeat them.

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 specifies the tool's function: evaluating ESG compliance of African trade finance providers using WITS and CDP data, and returning a breakdown across environmental, social, and governance dimensions. This distinguishes it from sibling ESG tools by focusing on a specific target (African trade finance) and methodology.

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 usage context: 'Ideal for due diligence on trade partners or portfolio risk assessment.' It does not explicitly name alternative tools or exclusion criteria, but the use case is specific enough for an agent to make an informed choice.

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

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.