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rollback_prompt

Revert the autogenerated portion of a prompt to a previous version while preserving user-customized content. Requires confirmation before execution.

Instructions

Revertir prompt a version anterior — Revierte la parte autogenerada del prompt a una version anterior del historial. La parte personalizada del usuario se mantiene. FLUJO DE CONFIRMACION: Esta accion devolvera requires_confirmation=true con success=false - esto NO es un error, es el flujo normal. Cuando recibas esto, describe brevemente al usuario que version se va a restaurar y PARA. NO llames de nuevo a esta accion. El sistema mostrara botones automaticamente. [mutation] (requiere confirmación: pasar confirm=true para ejecutar)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
version_idYesID de la version a restaurar. Obtenerlo llamando a get_prompt_history primero
confirmNoPasar true para confirmar la ejecución de esta acción peligrosa
Behavior4/5

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

Without annotations, the description carries full burden and discloses: mutation nature ([mutation] tag), dangerous operation status ('acción peligrosa'), two-step confirmation behavior (returns requires_confirmation=true with success=false initially), and side effects (system shows automatic buttons). Minor gap on irreversibility or history creation.

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?

Well-structured with purpose first, scope clarification second, and detailed confirmation flow third. All sentences serve the goal of guiding the agent through a complex stateful workflow. Slightly cluttered by inline tags ([mutation]) but efficiently packed with necessary guidance.

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?

No output schema exists, so the description appropriately explains the return behavior (requires_confirmation=true with success=false is normal flow) and instructs on UI delegation. Covers mutation characteristics, confirmation requirements, and sibling differentiation adequately for a stateful operation.

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

Parameters4/5

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

While schema has 100% coverage documenting the parameters, the description adds critical workflow context that the 'confirm' parameter executes a dangerous action and explains the confirmation flow logic, helping the agent understand why and when to set confirm=true.

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 specific action (revertir/revierte) on the auto-generated prompt part, explicitly distinguishes scope by noting user-customized parts are preserved (differentiating from restore_default_prompt), and identifies the target resource (prompt version history).

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

Usage Guidelines5/5

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

Provides explicit workflow guidance for the two-step confirmation flow ('FLUJO DE CONFIRMACION'), instructs exactly when to stop ('NO llames de nuevo a esta accion' when requires_confirmation=true), and describes the UI behavior ('El sistema mostrara botones automaticamente'). Clearly distinguishes use case from alternatives via scope limitations.

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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