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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
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.
esgFocusAreasYes
industrySectorNo
procurementObjectivesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
alignmentScoresNo
recommendationsNo
benchmarkComparisonNo
overallAlignmentScoreNo

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnly, openWorld, and idempotent hints; the description does not contradict them. It adds methodological context (GRI, EU TED) but no additional behavioral details such as data sourcing caveats, latency, or rate limits, so value beyond the annotations is modest.

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?

Three functional sentences front-load the purpose, inputs, and outputs, but the trailing keyword list is redundant with the body and adds little value. The description is compact and scannable overall.

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 an output schema present and annotations covering safety, the description provides sufficient orientation: what inputs are expected, what analysis is performed (GRI, EU TED), and what outputs are produced. It omits optional parameter handling and limitations, but those are secondary; the core context for a COO user is present.

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 only 25% (async described), and the description partially compensates by naming the two required inputs ('procurement objectives' and 'ESG focus areas') and giving examples (carbon reduction, supplier diversity). It does not explain procurementObjectives structure (id, weight) or the optional industrySector field, leaving a gap.

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 opens with a specific verb-resource pair: 'Aligns procurement OKRs with ESG targets' and adds methodology (GRI standards, EU TED benchmarks) plus outputs (alignment scores, gap analysis, recommendations). This clearly distinguishes it from sibling ESG tools like hr_benefits_esg_aligner or action_plan_esg by focusing on procurement and COOs.

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?

It identifies target users ('COOs integrating sustainability into procurement strategy') and the context of procurement objectives with ESG focus areas, which implies when to use. However, it does not explicitly name alternatives or state when not to use it, unlike a best-practice exclusion.

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.