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mark_all_notifications_read

Mark all unread WhatsApp notifications as read with a single mutation call.

Instructions

Marcar todas como leidas — Marca todas las notificaciones no leidas como leidas [mutation]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idNoID del agente (opcional)
limitNoMaximo de resultados
offsetNoPosicion de inicio
filterNoFiltro de notificaciones
typeNoTipo de notificacion
notification_idNoID de la notificacion
Behavior3/5

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It states it is a mutation and marks notifications as read, but does not mention any side effects, permissions required, or whether the action is reversible. The description is adequate but minimal, missing details like if it only affects current user's notifications or all in the system.

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 very concise, consisting of a single short sentence followed by a bracketed mutation indicator. It is front-loaded with the key action. However, it could be slightly improved by using a more structured format or including a brief note about filter usage.

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 6 parameters and no output schema, the description should explain how parameters interact with the 'mark all' behavior. It fails to do so, leaving ambiguity about whether it truly marks all or respects filters. The tool's complexity is not adequately addressed, making it incomplete for effective agent usage.

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

Parameters2/5

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

The input schema has 6 parameters with 100% description coverage, so baseline is 3. However, the description does not clarify how parameters like 'limit', 'offset', 'filter', and 'type' apply to a 'mark all' operation, which is confusing. The presence of these parameters suggests selective marking, contradicting the 'all' claim. This reduces the value added by the description.

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 it marks all unread notifications as read, with the verb 'mark' and resource 'all notifications'. It explicitly includes '[mutation]' to indicate it is a state-changing operation. The tool name and description distinguish it from the sibling 'mark_notification_read' which suggests a single notification.

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?

The description indicates a bulk operation but does not provide explicit guidance on when to use it versus alternatives like 'mark_notification_read'. Given the sibling list includes both, it would be helpful to mention that for marking individual notifications, the other tool should be used. The lack of this guidance reduces clarity for an AI agent.

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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