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get_conversation_count

Count WhatsApp conversations by search criteria, date range, or predefined period to analyze messaging volume and track communication patterns.

Instructions

Contar conversaciones — Cuenta conversaciones que coinciden con criterios de busqueda, fecha o periodo [query]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoTexto a buscar
periodNoPeriodo predefinido
date_fromNoFecha inicio YYYY-MM-DD
date_toNoFecha fin YYYY-MM-DD
phoneNoFiltrar por telefono del cliente
limitNoMaximo de resultados
offsetNoPosicion de inicio para paginacion
hoursNoUltimas N horas
conversation_idNoID de conversacion especifica
last_nNoUltimos N mensajes
agent_idNoID del agente
messageNoTexto del mensaje a enviar o eliminar
formatNoFormato de respuesta
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to state whether this is a read-only operation, what data structure is returned (integer vs object), or how pagination parameters (limit/offset) interact with a count operation—which is atypical and confusing.

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 efficiently front-loaded with the action verb and resource. However, the trailing '[query]' tag feels like a formatting artifact or incomplete thought rather than integrated documentation, slightly diminishing the structural quality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 13 filter parameters, no output schema, and the presence of unusual parameters for a count operation (limit, offset, last_n, message), the description is insufficient. It fails to explain the return format, pagination behavior, or resolve ambiguity around whether this returns a total count or a limited result set.

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 has 100% description coverage, establishing a baseline of 3. The description mentions '[query]' which loosely references the search capability, but adds no syntax details, validation rules, or guidance on parameter precedence when conflicting filters (e.g., 'period' vs 'date_from') are provided.

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?

The description clearly states the tool counts conversations ('Contar conversaciones') matching search criteria, dates, or periods. However, it fails to distinguish this from the sibling tool 'search_conversations', which likely retrieves the actual conversation data rather than just the count.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'search_conversations' or 'get_conversations_summary'. There is no mention of prerequisites, required parameter combinations, or when counting is preferred over retrieving full records.

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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