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vendor_esg_blacklist_monitor

Read-onlyIdempotent

As a COO, quickly check if a vendor is blacklisted for ESG non-compliance using CDP and GRI data. Input the vendor's legal name or identifier to receive their ESG risk score, blacklist status, and compliance violations. Returns structured data including CDP disclosure score, GRI alignment, and any regulatory flags. Ideal for vendor due diligence, risk assessment, and sustainability reporting. Keywords: ESG, vendor risk, compliance, CDP, GRI, sustainability, blacklist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoReporting year (default: current year)
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.
vendorIdNoOptional identifier (e.g., LEI, DUNS)
vendorNameYesLegal name of the vendor to check

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesYes
vendorIdNo
warningsYes
griAlignedNo
vendorNameYes
violationsNo
blacklistedYes
esgRiskScoreNo
cdpDisclosureScoreNo

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, and idempotent. Description adds that it uses CDP/GRI data and returns specific structured output fields, providing additional context about data sources and result contents.

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?

Description is three sentences plus keyword list, front-loaded with 'quickly check if a vendor is blacklisted'. No wasted words, though keywords are slightly redundant.

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?

With output schema present and read-only annotations, the description sufficiently covers purpose, data sources, and use cases. No need to detail return values since output schema exists. Slight lack of error handling info, but acceptable.

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?

All parameters have schema descriptions (100% coverage). The description mentions vendor legal name or identifier but adds no new semantics beyond schema; it doesn't explain year or async behavior.

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?

Description clearly states it checks if a vendor is blacklisted for ESG non-compliance using CDP and GRI data, and specifies outputs like ESG risk score, blacklist status, and compliance violations. This is a specific verb+resource+scope that distinguishes from sibling vendor risk tools.

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?

States 'Ideal for vendor due diligence, risk assessment, and sustainability reporting', giving clear context for when to use. Does not explicitly name alternatives or exclusions, so not 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

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.