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mcp-knowledge

by io.github.getgapup

vendor_esg_diversity_scanner

Read-onlyIdempotent

For COOs: scans vendor ESG reports to identify suppliers lacking diversity disclosures in GRI or CDP filings. Input a supplier name or identifier to receive a structured assessment of gender, ethnicity, and board diversity metrics. Returns compliance gaps, missing data flags, and source references from CDP open data and GRI standards. Ideal for vendor risk assessment and ESG compliance tracking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoReporting year to check (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.
supplierIdNoCDP or GRI identifier for the supplier (e.g., CDP company ID)
supplierNameYesExact or partial name of the supplier to scan

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
reportLinksNoURLs to relevant ESG reports
supplierNameYes
complianceScoreYesPercentage compliance with diversity disclosure standards
diversityDisclosuresYes

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, idempotentHint. The description adds value by specifying data sources ('CDP open data and GRI standards') and output details ('compliance gaps, missing data flags, source references'). No contradiction 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?

Three sentences, each adding value: target user, action/input, output/use case. Front-loaded with 'For COOs' and efficient wording with no redundancy.

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?

Has output schema, so description doesn't need to detail return values. It mentions the key outputs (structured assessment, gaps, flags, references) and data sources, which is sufficient for the tool's complexity.

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 baseline is 3. The description reinforces using 'supplier name or identifier' (matching supplierName and supplierId) but does not add new semantics beyond what the schema already provides. The async parameter is not mentioned.

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 uses specific verbs ('scans', 'identify', 'returns') and clearly states it targets diversity disclosure gaps in ESG reports from GRI or CDP. It distinguishes from sibling tools like 'supplier_esg_audit' or 'vendor_risk_assessor' by focusing specifically on diversity metrics and missing data flags.

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 explicitly targets COOs and states ideal use cases ('vendor risk assessment', 'ESG compliance tracking'). However, it does not provide when-not-to-use or mention alternative tools, which would improve differentiation given many sibling tools.

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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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