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Glama

Tablero del día (parte diario visual)

ml_tablero
Read-only

Builds a visual daily dashboard that consolidates team insights, sales numbers, and urgent tasks, showing actionable resolution steps for issues needing attention.

Instructions

Arma el tablero visual del día con todo lo que saben los 19 trabajadores (incluido el ranking de nichos de Emma): la frase del día, lo que está funcionando, lo que necesita atención (urgente primero, con la skill para resolverlo), tus números (facturación, neto, ganancia, publicidad, reputación, pendientes), la planilla del equipo (tocás un trabajador y ves su tabla), lo que viene, la evolución de 30 días y la bitácora. Es una página local (sin servidor, funciona sin internet) con tutorial guiado; después se actualiza sola con cada control del equipo. Con abrir=true la abre en el navegador.

Input Schema

NameRequiredDescriptionDefault
abrirNotrue = abrirla en el navegador de esta computadora

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.30.0-tyl.1

TDQS

A3.6/5.0
Behavior4/5

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

Beyond readOnlyHint=true, the description discloses meaningful behavior: it is a local page, works without internet, has a guided tutorial, and updates automatically with each team control. It does not specify what is returned when abrir is false or whether a file is written, leaving minor behavioral ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded and nearly all content is relevant, but the first sentence is an extremely long run-on enumeration. It would be more scannable if the dashboard sections were structured or shortened instead of packed into one dense clause chain.

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 a simple one-parameter tool with no output schema, the description is rich about what the dashboard contains and how it behaves offline. It still does not clarify the return/result when abrir is false, which matters slightly because no output schema exists.

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 description coverage is 100%, and the schema already explains that 'abrir' opens the page in the browser. The description repeats this ('Con abrir=true la abre en el navegador') but adds no new meaning beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Arma el tablero visual del día' and then enumerates the dashboard contents. It is clearly a daily visual dashboard, but it does not explicitly distinguish itself from siblings such as ml_panel_ventas, ml_metricas, or ml_numeros.

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?

Usage is implied by the daily overview content and by 'Con abrir=true la abre en el navegador', but there is no explicit when-to-use guidance or comparison with alternative summary/metrics tools. An agent can infer the purpose, but must decide on its own when this is preferable to sibling dashboard tools.

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