gapup-mcp

dora_operational_resilience_stress_tes

Read-onlyIdempotent

Assess DORA operational resilience by simulating ICT failure scenarios for financial entities. Designed for legal/compliance teams to evaluate ICT risk management under DORA Article 25. Inputs include failure scenario parameters (e.g., ICT service type, duration, impact radius) and entity profile. Outputs structured resilience scores, regulatory gaps, and mitigation recommendations with EUR-Lex/FTC enforcement references.

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.
`entityType`	Yes
`impactRadius`	Yes
`ictServiceType`	Yes
`existingMitigations`	No
`failureDurationHours`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`sources`	Yes
`warnings`	No
`regulatoryGaps`	Yes
`resilienceScore`	Yes
`simulationTimestamp`	No
`recommendedMitigations`	Yes

TDQS

A3.9/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, so the tool is understood as a safe, read-only simulation. The description adds context about outputs (resilience scores, regulatory gaps, recommendations) and inputs, but does not disclose side effects or performance characteristics beyond what annotations cover.

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 concise (two sentences) and front-loaded with the core purpose. Every sentence adds value, covering purpose, target audience, regulation, inputs, and outputs without fluff.

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 (6 parameters, 4 required, enums, output schema) and the presence of an output schema (which reduces the need to explain return values), the description covers most aspects: purpose, regulation, target users, and output types. It lacks elaboration on parameter details and async behavior, but these are partially covered in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 17% (only the async parameter has a description). The description lists some parameter examples ('ICT service type, duration, impact radius') but does not explain the enum values or other parameters like 'existingMitigations'. This leaves significant ambiguity about parameter semantics.

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 action ('Assess DORA operational resilience by simulating ICT failure scenarios') and identifies the target users (legal/compliance teams) and regulatory context (DORA Article 25). It distinguishes itself from sibling tools like 'dora_metrics_deep_dive' by focusing on simulation and regulatory gap analysis.

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 explicitly states when to use the tool (for evaluating ICT risk management under DORA Article 25) and who it's designed for (legal/compliance teams). However, it does not mention when not to use it or offer alternatives, which would improve clarity further.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

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