Feedforward Controls Skill

Purpose

Establishes a production-grade proactive control framework for AI agent execution. Feedforward controls operate on the principle that planning, validation, and constraint analysis BEFORE action produces superior outcomes compared to reactive correction. This system implements structured observation-orientation-decision-action cycles, hierarchical task decomposition, intent classification pipelines, pre-flight validation gates, and anticipatory error prevention mechanisms. The goal is to minimize wasted computation, prevent invalid actions, and ensure agents pursue well-structured plans aligned with user intent.

Core Principles

1. Plan Before Execute: Every agent action must be preceded by an explicit planning phase. No execution without a validated plan artifact.
2. Constraint Propagation First: Propagate constraints through the entire plan tree before committing to any action. Early constraint violations prevent cascading failures.
3. Intent Alignment Gate: Classify and confirm user intent before decomposing goals. Misclassified intent poisons the entire execution pipeline.
4. Hierarchical Decomposition: Break complex goals into atomic sub-tasks with clear preconditions, postconditions, and dependency edges. Never execute monolithic plans.
5. Anticipatory Validation: Simulate execution paths mentally before committing resources. Pre-flight checks catch errors at zero cost compared to runtime failures.

Agent Protocol