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mcp-knowledge

by io.github.getgapup

working_capital_esg_impact_rater

Read-onlyIdempotent

As a CFO, assess how ESG factors (Environmental, Social, Governance) influence working capital efficiency using IMF SDR and BIS data. Inputs include company sector, geographic exposure, and ESG risk scores. Outputs provide a quantitative impact rating on working capital metrics like days sales outstanding (DSO) and inventory turnover, alongside IMF SDR-aligned liquidity risk indicators.

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.
regionYesPrimary geographic exposure (e.g., 'EU', 'APAC')
sectorYesIndustry sector (e.g., 'manufacturing', 'energy')
currencyNoReporting currency (ISO 4217 code, e.g., 'USD', 'EUR')
esgRiskScoreYesAggregate ESG risk score (0-100)
workingCapitalRatioNoCurrent working capital ratio (current assets / current liabilities)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
impactRatingNoESG impact on working capital efficiency (-100 to +100)
esgFactorBreakdownNo
liquidityRiskIndicatorNoIMF SDR-aligned liquidity risk score (0-1)
workingCapitalAdjustmentNoProjected adjustment to working capital ratio (%)

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds context about data sources (IMF SDR, BIS) and output types, but does not disclose rate limits, caching, or other behavioural traits. It is consistent with annotations (no contradiction).

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?

Two sentences, each adds value. Front-loaded with the purpose ('assess how ESG factors influence working capital efficiency'). No wasted words. Appropriate length given the tool's complexity.

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 6 parameters and an output schema, the description covers the key aspects: inputs, outputs, and data sources. It is complete enough for an AI agent to understand the tool's role, though it could briefly mention the output schema exists.

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 all parameters have descriptions in the schema. The tool description adds meaning by listing some inputs (sector, region, esgRiskScore) and mentioning output concepts like DSO and liquidity risk, but does not describe parameters not mentioned (async, currency, workingCapitalRatio). Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose clearly: assesses how ESG factors influence working capital efficiency using specific data sources (IMF SDR, BIS). It lists inputs and outputs, but does not differentiate from sibling tools like 'working_capital' or 'esg_audit_multi', so it is not a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description addresses a CFO persona and lists inputs, but provides no guidance on when to use this tool versus alternatives. Siblings like 'working_capital' and 'esg_audit_multi' exist, and no exclusions or context for selection are given.

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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