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nis2_supply_chain_dependency_map

Read-onlyIdempotent

Generates a visual dependency map of supply chain relationships under the NIS2 Directive, scoring criticality based on regulatory sources like EUR-Lex and CNIL decisions. Designed for legal and compliance teams to identify high-risk third-party dependencies. Inputs include organization identifiers and optional scope filters. Outputs structured dependency data with criticality scores and regulatory references.

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.
depthNoDependency chain depth to analyze
scopeNoAnalysis scope: full supply chain or critical dependencies only
sectorNoNIS2 sector classification (e.g., 'energy', 'transport')
organizationIdYesUnique identifier for the organization (e.g., VAT number or LEI)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
dependenciesNo

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, and idempotentHint, so the description need only add context. It adds that criticality is scored using regulatory sources like EUR-Lex and CNIL decisions, and that outputs include criticality scores and regulatory references. This goes beyond the annotations and gives the agent useful behavioral expectations.

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?

The description is three sentences, front-loaded with the core action, then target audience, then input/output summary. It contains no redundant or filler content. Every sentence contributes to understanding the tool's purpose and usage.

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?

With a rich input schema (100% coverage), a declared output schema, and annotations covering safety and idempotency, the description provides sufficient context for an agent to select and invoke the tool. It mentions regulatory sources, intended users, and outputs, which together make the tool's role clear without needing to restate schema details.

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?

The input schema has 100% description coverage, so the baseline is 3. The description only summarizes that inputs include 'organization identifiers and optional scope filters,' which adds no meaning beyond the schema. It does not elaborate on depth, sector, or async behavior, but the schema already documents these sufficiently.

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 states a specific verb and resource: 'Generates a visual dependency map of supply chain relationships under the NIS2 Directive.' It further specifies that it scores criticality based on regulatory sources, which distinguishes it from generic supply chain or vendor risk tools. The mention of being 'Designed for legal and compliance teams' clarifies its intended domain.

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 provides clear context: it is for legal and compliance teams to identify high-risk third-party dependencies under NIS2. However, it does not explicitly mention alternatives or when not to use this tool, so it lacks exclusionary guidance. The intended use case is clear enough to guide an agent.

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.