Skip to main content
Glama

sovereign_data_breach_impact

Read-onlyIdempotent

Estimates financial impact of a data breach across three jurisdictions (US, EU, UK) for CFO strategic planning. Inputs include breach size, industry sector, and affected jurisdictions. Outputs include direct costs, regulatory fines, reputational damage, and cyber insurance premium adjustments. Ideal for cross-border risk assessment, financial contingency planning, and board-level reporting. Keywords: data breach cost, regulatory fines, cyber insurance, financial risk, cross-jurisdiction impact.

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.
industryNoIndustry sector of the affected organization
records_lostYesNumber of records compromised in the breach
jurisdictionsYesJurisdictions where the breach has legal or financial impact
detection_time_daysNoTime in days to detect the breach

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
total_cost_usdNoEstimated total financial impact in USD
cost_per_record_usdNoCost per compromised record in USD
regulatory_fines_usdNo
cyber_insurance_impactNo
reputational_damage_usdNoEstimated reputational damage cost in USD

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the bar is lower. The description adds that the tool 'estimates' rather than retrieves actual data and lists output categories (direct costs, regulatory fines, etc.), which is useful context. However, it doesn't disclose limitations, data sources, or calculation methodology, so it remains a moderately transparent description.

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 plus a keyword list, front-loaded with the core purpose. Every sentence earns its place—purpose, inputs/outputs, and use cases—with no filler or redundancy.

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 output schema exists, return values need no explanation. The description covers purpose, inputs, outputs, and ideal use cases, which is sufficient for a read-only estimation tool. It lacks caveats or limitations, but the description is complete enough for an agent to decide when to invoke the tool.

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 each parameter is already documented. The description mentions 'breach size, industry sector, and affected jurisdictions,' which maps to records_lost, industry, and jurisdictions, but adds no new meaning beyond what the schema provides. Baseline 3 is appropriate.

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: 'Estimates financial impact of a data breach across three jurisdictions (US, EU, UK) for CFO strategic planning.' This specific verb+resource+scope distinguishes it from general data breach tools. It also enumerates inputs and outputs, making the purpose unmistakable.

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 with 'Ideal for cross-border risk assessment, financial contingency planning, and board-level reporting.' This tells when to use it, but it does not mention alternatives or explicit exclusions, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.