Skip to main content
Glama

creg_relaciones

Read-onlyIdempotent

Trace a norm's regulatory history: its source, what it repeals or modifies, who amended it, and related projects or concepts, with citations and document links.

Instructions

Muestra de dónde viene una norma, qué deroga o modifica y quién la derogó o modificó.

Sale de grafo.py, que lee las cláusulas de los propios textos (deroga, modifica, adiciona, sustituye, "derogado por" en las anotaciones del Gestor, y las leyes invocadas en el preámbulo). Cada relación trae la cita y la ruta del documento para abrirlo.

NO sustituye la lectura: para citar una norma, aunque sea para decir que está derogada, abrir su documento con creg_leer_documento. Esto dice dónde mirar; la cita sale de lo leído.

Args: params (RelacionesInput): norma ('174 de 2021' o ruta) y profundidad (1-3).

Returns: str: Árbol en texto con fundamento, predecesoras, reemplazos, proyectos y conceptos que la mencionan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With annotations already declaring readOnlyHint, idempotentHint, and destructiveHint=false, the description adds substantial behavioral context: it explains the data source (grafo.py reading clauses, annotations, and preamble invocations) and states that each relationship includes the citation and document path needed to open it. It also describes the return structure (fundamento, predecesoras, reemplazos, proyectos, conceptos).

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 front-loaded with the core purpose and is structured into useful sections (source, warning, Args, Returns). It is somewhat long due to internal implementation detail about grafo.py, but most sentences earn their place by clarifying provenance, limitations, or output shape.

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?

Despite an output schema existing, the description helpfully explains the return tree's categories and emphasizes that citations must be read from the source document. Combined with annotations covering safety and idempotence, this gives the agent enough context 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.

Parameters3/5

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

The input schema already documents norma's accepted formats and profundidad's 1-3 depth semantics in detail, so the description's Args line ('norma ... y profundidad (1-3)') only restates them at a high level. The description adds no new format or behavior detail beyond the schema, making the baseline 3 appropriate where schema text carries the meaning.

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 ('Muestra') and resource ('de dónde viene una norma, qué deroga o modifica y quién la derogó o modificó'), making the tool's purpose concrete. It also distinguishes itself from the sibling creg_leer_documento by warning that it does not replace reading the source document.

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?

It explicitly tells the agent when not to use it and what to use instead: 'NO sustituye la lectura: para citar una norma, aunque sea para decir que está derogada, abrir su documento con creg_leer_documento.' It also identifies the tool's role as showing where to look, not providing the citation itself.

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