ai-domain-energy-demand-forecasting-skill-2026

name	ai-domain-energy-demand-forecasting-skill-2026
description	Despliega soluciones de IA para energy demand forecasting con arquitectura modular, metricas auditables y decisiones alineadas al contexto del dominio.
version	1.0.0
domain	domain-ai
quality_tier	expert
compatibility	["claude-code","codex"]
owner	yonatanguerrerosoriano
tags	["domain-ai","industry-ai","automation","decision-systems","2026"]
foundation_skills	["optimization-foundations","probability-foundations","statistics-inference-foundations","testing-verification-foundations","security-threat-modeling-foundations","debugging-causal-reasoning-foundations"]

Ai Domain Energy Demand Forecasting Skill 2026 Skill

Mission

Despliega soluciones de IA para energy demand forecasting con arquitectura modular, metricas auditables y decisiones alineadas al contexto del dominio.

When to use

• When the user asks for a repeatable workflow in this domain.
• When a specialized checklist improves speed or quality.

Inputs expected

• Task objective and expected output.
• Relevant files, paths, or system constraints.
• Any non-negotiable requirements (security, style, deadlines).

Workflow

1. Understand scope, assumptions, and risks.
2. Execute the workflow in a deterministic order.
3. Verify outcomes and report any limitations clearly.

Output contract

Provide results in this order: key outcome, concrete changes, validation status, next steps.

Guardrails

• Never fabricate facts, outputs, or tool results.
• Ask for confirmation before destructive operations.
• Prefer minimal, reversible changes when uncertain.

Foundations

• optimization-foundations
• probability-foundations
• statistics-inference-foundations
• testing-verification-foundations
• security-threat-modeling-foundations
• debugging-causal-reasoning-foundations

Logical reliability checklist

• Assumptions are explicit and separated from verified facts.
• The solution path is justified with clear reasoning steps.
• Edge cases and contradiction checks are included.
• Output is testable, auditable, and reversible when possible.

Example prompts

• "Apply the ai-domain-energy-demand-forecasting-skill-2026 skill to handle this task end-to-end."
• "Run ai-domain-energy-demand-forecasting-skill-2026 and produce a production-ready output with validation notes."