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Generar informe de compliance estructurado

gobernador_generate_compliance_report
Read-onlyIdempotent

Generates an executive compliance report for AI systems, summarizing findings by severity and framework, and linking related ontology concepts. Ideal for client-facing reports or internal pre-launch reviews.

Instructions

Genera un informe ejecutivo de compliance para un sistema de IA, agregando hallazgos por severidad y framework, más los conceptos de la ontología relacionados a cada hallazgo.

Este es el tool de mayor nivel: internamente corre el mismo motor que gobernador_audit_text pero agrega resumen ejecutivo y deduplica hallazgos, pensado para entregarse como base de un informe a cliente o para revisión interna previa a lanzamiento.

Args:

  • system_description (string): descripción completa del sistema (mínimo 20 caracteres)

  • frameworks (opcional): array con 'ley_21719' | 'iso_42001' | 'eu_ai_act'. Si se omite, evalúa los tres.

Returns: JSON con: { "summary": { "totalFindings": number, "bySeverity": {...}, "byFramework": {...} }, "findings": [ {...} ], "relatedConcepts": [ { "id", "name", "description" } ], "disclaimer": string }

Ejemplos de uso:

  • Describir un sistema completo de scoring crediticio con datos de terceros y servidores en el extranjero -> informe con hallazgos en las 3 normativas, priorizados por severidad

No usar cuando: solo se necesita chequear un fragmento de texto puntual — usar gobernador_audit_text para eso (más rápido y granular).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frameworksNoLista de frameworks a incluir en el informe. Si se omite, incluye los tres.
system_descriptionYesDescripción completa del sistema de IA: propósito, tipos de datos que procesa, decisiones que toma, usuarios afectados, proveedores/infraestructura involucrada.
Behavior4/5

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

The description explains that the tool internally runs the same engine as audit_text but adds an executive summary and deduplicates findings. It aligns with annotations (readOnlyHint, idempotentHint, destructiveHint) and provides additional context about aggregation behavior.

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 well-structured with a clear purpose, internal workings, argument details, examples, and a usage guideline. It is slightly verbose in repeating schema descriptions but overall each section adds value.

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?

The description covers all necessary aspects: purpose, differentiation from siblings, parameter details with examples, return structure (since no output schema), and usage guidelines. It provides sufficient information for an agent to select and invoke the tool correctly.

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

Parameters4/5

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

Schema coverage is 100% with descriptions, and the description adds further context: system_description requires at least 20 characters and should include purpose, data types, decisions, users, etc. Frameworks are clarified with allowed values and default behavior (all three if omitted).

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 generates a structured compliance report for AI systems, aggregating findings by severity and framework. It distinguishes itself from siblings by being the highest-level tool that adds executive summary and deduplicates findings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when not to use this tool (e.g., for checking a specific text fragment) and recommends gobernador_audit_text as a faster alternative. It also implies use cases like client reports or internal pre-release reviews.

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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