mcp-knowledge

procurement_okr_esg_aligner

Read-onlyIdempotent

Aligns procurement OKRs with ESG targets for COOs using GRI standards and EU TED procurement benchmarks. Inputs include procurement objectives and ESG focus areas (e.g., carbon reduction, supplier diversity). Outputs structured alignment scores, gap analysis, and actionable recommendations. Essential for COOs integrating sustainability into procurement strategy. Keywords: procurement, ESG, GRI, EU TED, OKR alignment, sustainability metrics.

Input Schema

TableJSON Schema

Name	Required	Description
`async`	No	If 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.
`esgFocusAreas`	Yes
`industrySector`	No
`procurementObjectives`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`sources`	No
`warnings`	No
`alignmentScores`	No
`recommendations`	No
`benchmarkComparison`	No
`overallAlignmentScore`	No

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, which the description reinforces by describing an analytical (non-mutating) operation. However, the description does not disclose additional behavioral traits such as asynchronous execution (async parameter present but not mentioned) or any rate limits/pagination, so it adds only limited value beyond annotations.

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 4 sentences plus keywords, with the main purpose front-loaded. Every sentence adds value, though the keyword list at the end is slightly redundant. Overall, it is well-structured and avoids unnecessary verbosity.

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's complexity (4 params, output schema exists), the description covers the core functionality, inputs, and outputs. It mentions standards and benchmarks for credibility. The presence of an output schema means return values need not be detailed. However, the async parameter and industrySector are not addressed, slightly reducing completeness.

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 (25%), with only 'async' having a description. The description text partially compensates by naming 'procurement objectives' and 'ESG focus areas' and giving examples (carbon reduction, supplier diversity). However, it does not explain 'industrySector' or the structure of 'procurementObjectives' (objects with id, description, weight), leaving gaps.

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 aligns procurement OKRs with ESG targets using specific standards (GRI, EU TED). It specifies inputs (procurement objectives, ESG focus areas) and outputs (alignment scores, gap analysis, recommendations). This provides a specific verb and resource, differentiating it from generic alignment tools.

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

Usage Guidelines3/5

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

The description identifies the target user (COOs integrating sustainability) and implies usage context, but does not explicitly state when to use this tool over alternatives or mention exclusions. No sibling differentiation is provided, leaving usage guidance implied rather than explicit.

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.

procurement_okr_esg_aligner

Input Schema

Output Schema

TDQS

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TDQS

Resources