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apply_training_suggestion

Apply an AI training suggestion to create a knowledge snippet or update assistant prompt based on suggestion level. Requires confirmation to execute.

Instructions

Aplicar sugerencia de entrenamiento — Aplica una sugerencia de entrenamiento de IA. Segun el nivel, crea un snippet de conocimiento o actualiza el prompt del asistente. [mutation] (requiere confirmación: pasar confirm=true para ejecutar)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
suggestion_idYesID de la sugerencia a aplicar
confirmNoPasar true para confirmar la ejecución de esta acción peligrosa
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is a mutation requiring confirmation and has conditional behavior based on level. However, it lacks details on side effects, reversibility, or required permissions.

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 very concise with two sentences, front-loading the action and key details. No redundant information.

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

Completeness3/5

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

Given the tool's complexity (mutation with conditional behavior), no output schema, and full schema coverage, the description explains the conditional outcome but omits what 'level' refers to and does not cover error states or return values.

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%, so baseline is 3. The description adds no new meaning beyond what the schema already provides for suggestion_id and confirm.

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 applies a training suggestion and specifies the conditional outcomes (creates knowledge snippet or updates assistant prompt). This distinguishes it from siblings like apply_prompt_instruction or edit_knowledge_snippet.

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 mentions the requirement for confirmation (confirm=true) and hints at mutation via [mutation] tag, but does not explicitly state when to use this tool versus alternatives like apply_prompt_instruction or when not to use it.

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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