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JuanDsm04

finanzas-pyme

by JuanDsm04

desglose_gastos

Break down monthly expenses by category, revealing totals, percentages, fixed vs variable costs, top suppliers, and largest transactions. Know exactly where your money went each month.

Instructions

Desglosa los gastos de un mes por categoria (proveedores, nomina, servicios, etc.).

Responde preguntas como "cuanto gaste en julio" o "en que se me fue el dinero el mes pasado". Devuelve el total, el reparto por categoria con porcentajes, la separacion entre gastos fijos y variables, los principales proveedores y los movimientos individuales mas grandes.

Args: mes: Mes a analizar en formato 'YYYY-MM' (ej. '2026-08'). Si se omite, se usa el ultimo mes con datos registrados. incluir_comparacion: Si es True, agrega la comparacion contra el mes anterior y contra el promedio de los tres meses previos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mesNo
incluir_comparacionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It transparently explains the output (total, categories, fixed/variable, top vendors, largest transactions) and parameter behavior (default for 'mes', effect of 'incluir_comparacion'). It does not mention side effects, but as a read-only analysis tool, none are expected.

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 efficiently structured: a one-sentence summary, example questions, a list of output components, and parameter explanations. Every sentence adds value, and there is no redundancy.

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 having an output schema (not shown in detail), the description provides a high-level list of return elements, making it clear what the user will get. It also covers parameter defaults and example use cases, making it complete for a two-parameter read-only tool. No critical information is missing.

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

Parameters5/5

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

The schema provides zero descriptions for the two parameters. The description fully compensates by explaining the format and default behavior of 'mes' (YYYY-MM, defaults to last month with data) and the meaning of 'incluir_comparacion' (adds comparison to previous month and 3-month average), covering all 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 function with a specific verb ('Desglosa') and resource (expenses by month), and includes example questions that illustrate its use. It is contextually distinct from siblings which focus on anomalies, income trends, and projections.

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 by giving example queries ('cuanto gaste en julio') and outlining what the tool returns. However, it does not explicitly mention when to prefer this tool over the sibling tools or state exclusions, so it stops short of a perfect score.

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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