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from Education Agent Skills463
Creates scaffolded learning sequences moving from fully worked examples to independent practice using cognitive load theory.
This skill allows an agent to design a scientifically-backed instructional sequence for teaching procedures, algorithms, or multi-step processes. It generates a complete scaffold that starts with a fully annotated worked example, transitions through a series of 'completion problems' (where steps are progressively removed), and culminates in independent practice.
Use this skill when the goal is to teach a novice learner a complex procedure while minimizing extraneous cognitive load. It is ideal for subjects like mathematics, chemistry, or analytical writing where clear, step-by-step reasoning is essential.
Compatible with any agent supporting the Agent Skills standard, including Claude Code, Codex, Hermes, and other LLM-based agent frameworks.
This skill has not been reviewed by our automated audit pipeline yet.
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