learn-anything

Start or continue learning any skill — the primary interface to the meta-learning system.

Generate or regenerate learning materials for the active skill

Jump straight into a training session for your active skill.

Update an existing curriculum to reflect new developments in the field

Use this agent to generate assessment instruments: mastery gate items, delayed retention tests, and transfer tasks. Aligned to Bloom's levels with anti-gaming design. Dispatched by Material Forge.

Use this agent to generate SRS flashcard decks conforming to srs-cards.schema.json. Applies card design principles, anti-pattern rejection, visual audit, and color contrast enforcement. Dispatched by Material Forge.

Use this agent to generate inline SVG visuals for learning materials: concept illustrations, process flow diagrams, comparison diagrams, layered architecture diagrams, timelines, and annotated figures. Dispatched by Material Forge for each task class. Enforces WCAG color contrast rules.

Use this agent to generate worked examples with backward fading sequences for learning materials. Creates full solutions, self-explanation prompts, and progressive fading versions for each task class. Dispatched by Material Forge.

This skill should be used when the Learner Calibrator has produced the gap map and a learning plan needs designing. Applies 4C/ID whole-task instruction, Elaboration Theory epitome design, productive failure placement, and a seven-layer motivation architecture. Produces a sequenced curriculum with task classes, a dual-timeline schedule, assessment criteria, and plateau protocols. Includes a conversational checkpoint for epitome refinement with the learner. Output is structured JSON conforming to learning-plan.schema.json.

This skill should be used when the learning plan has been created (initial generation) or after each training session (update), or when the user asks to see their progress or dashboard. Generates and updates a React dashboard artifact that visualizes the learner's knowledge graph, curriculum progress, and key metrics. The dashboard is the learner's visual home base within the Claude Project, rendering an interactive knowledge graph with mastery overlay, curriculum roadmap, progress metrics, session history, and upcoming agenda.

This skill should be used when the user states a learning goal — any phrase like 'I want to learn X', 'teach me X', 'help me get better at X', or 'how do I learn X'. Classifies the skill type (motor/cognitive/perceptual/social), assesses the learning environment (kind vs. wicked), gathers the learner's background for transfer learning, and produces a constructive approach strategy. This is always the first step in the meta-learning pipeline. Output is structured JSON conforming to domain-assessment.schema.json.

This skill should be used when the Skill Researcher has produced a dependency graph and the learner's existing knowledge needs mapping. Walks through the graph conversationally, assessing mastery at key nodes using graph propagation and information-theoretic item selection to minimize questions needed. Produces the knowledge graph overlay (the 'gap map') that drives curriculum design. Output is structured JSON conforming to knowledge-graph.schema.json.

This skill should be used when the Curriculum Architect has produced a learning plan and learning materials need generating, or on-demand when the Training Conductor needs new materials, or when the user invokes '/materials'. Orchestrates dedicated subagents to generate worked examples with fading, visual materials, SRS flashcard decks, assessment instruments, reference one-pagers, dependency graph visualizations, productive failure scenarios, interleaved practice sets, and encoding aids. All outputs conform to the system's JSON schemas and are exportable to Anki (.apkg), PDF, and Markdown.