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Angelthebestone

Normativa Colombia MCP

Comparar dos artículos de normas distintas

comparar_articulos

Compares an article between two Colombian norms, marks added/deleted text, and categorizes differences by type (deadline, sanction, exception, subject, prohibition, obligation) or flags for review.

Instructions

Compara el texto de un artículo entre dos normas, marca lo añadido y lo eliminado, clasifica cada diferencia por patrones de texto (plazo, sanción, excepción, sujeto obligado, prohibición u obligación) y detecta cambios editoriales por similitud léxica (Dice bigramas, ≥0,92); lo que no encaja se marca «revisar manualmente». Sin modelo semántico.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
norma_aYesCita de la primera norma, ej. "Ley 909 de 2004"
norma_bYesCita de la segunda norma, ej. "Decreto 1083 de 2015"
articulo_aYesNúmero de artículo de la primera norma, ej. "12"
articulo_bYesNúmero de artículo de la segunda norma, ej. "12"

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.10.1

TDQS

A3.7/5.0
Behavior3/5

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

The description explains the core behavior (marking additions/deletions, classifying differences, detecting editorial changes, flagging manual review) but does not mention side effects, permissions, or rate limits. Since no annotations are provided, the description carries the burden and could be more explicit about read-only 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 a single dense sentence that packs substantial information without unnecessary verbosity. It is structured logically, though it could be split into clearer sentences for readability.

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?

There is no output schema, but the description gives a clear picture of the tool's behavior and expected outcome. It sufficiently describes the comparison, classification, and manual review flags, allowing an agent to infer what the result will look like.

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?

Schema coverage is 100% with all four parameters documented with examples. The description adds no additional parameter semantics beyond the schema, so it meets the baseline but provides no extra value.

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 verb 'Compara' (compare), specifies the resource (articles between two norms), and distinguishes it from sibling search/list tools by focusing on comparison and diff classification.

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

Usage Guidelines3/5

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

It describes the main function but does not explicitly state when to use this over alternatives like 'cambios_desde' or 'analizar_conflicto'. The phrase 'Sin modelo semántico' hints at a limitation but does not provide clear selection guidance.

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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