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procurement_six_sigma_waste_hunter

Read-onlyIdempotent

Analyzes procurement waste for COOs using Six Sigma DMAIC framework and EU TED tender data. Identifies non-value-added activities, overprocessing, and inefficiencies in procurement workflows. Inputs include procurement category, time period, and organizational unit. Outputs waste classification, cost impact estimates, and process improvement recommendations. — pass async:true REQUIRED to avoid x402 timeout.

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.
time_periodYesTime period for analysis (e.g., '2023-01-01/2023-12-31')
six_sigma_toolNoDMAIC
include_ted_dataNo
organizational_unitNoSpecific business unit or department (e.g., 'EMEA', 'Global Operations')
procurement_categoryYesSpecific procurement category to analyze (e.g., 'IT hardware', 'facilities')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
ted_data_coverageNo
cost_impact_estimateNo
waste_classificationNo
process_improvement_recommendationsNo

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and openWorld hints. The description adds value by explicitly requiring async:true to avoid x402 timeout and by disclosing output types (waste classification, cost impact estimates, recommendations). This complements the annotations without contradiction.

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 and front-loaded with the core purpose, followed by waste types and input/output summary. The appended async note is slightly awkward but necessary and justifiable. No redundant filler.

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 and safety annotations present, the description provides sufficient context: audience, data source, outputs, and the critical async requirement. It does not delve into six_sigma_tool options or include_ted_data behavior, but the schema's enums and defaults mitigate this gap.

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 67%, and the description names procurement category, time period, and organizational unit, but these are already documented in the schema. It does not explain six_sigma_tool or include_ted_data beyond what the schema offers (enum/default), though it adds contextual meaning for DMAIC and EU TED data.

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's function: analyzing procurement waste for COOs with Six Sigma DMAIC and EU TED tender data. It also specifies the types of waste identified (non-value-added activities, overprocessing, inefficiencies), which distinguishes it from generic analytics 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 implies appropriate usage context through audience (COOs), framework (Six Sigma), and data source (EU TED), but it does not explicitly state when to use this tool over alternatives or when not to use it. There are no exclusions or alternative tool references.

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.