Documentation

Install the CLI, author a course, review its content, import a draft, and confirm publication.

Conceptual overview of the adaptive learning engine — the 7 core principles, two-YAML workflow, and system architecture.

Consistent definitions for every platform concept — from Academy to XP. Essential reference for humans and AI agents.

Step-by-step guide to building a course on Graspful. Content-agnostic — works for any subject.

Full YAML schema reference for courses — sections, concepts, knowledge points, problems, and prerequisite edges.

YAML schema for white-label brands — theme presets, landing page configuration, SEO, and pricing.

The 10 mechanical quality checks that every course must pass before publishing.

Brand colors, typography, spacing, and component patterns. The visual system behind every Graspful brand.

Full reference for every graspful command: validate, import, publish, review, create, fill, describe, and login.

Set up the MCP server for Claude Code, Cursor, Codex, and VS Code. Tool schemas and configuration examples.

Prerequisites, encompassing edges, and the knowledge frontier that drives adaptive learning.

Bayesian Knowledge Tracing, estimated mastery, and prerequisite rules for progression.

MEPE question selection and evidence propagation — how 20-60 questions map student knowledge.

The FIRe algorithm, implicit repetition via encompassing edges, and exponential memory decay.

Priority-based system that chooses lessons, reviews, or remediation — whatever the student needs most.

XP calibrated to ~1 point per minute, streaks, leaderboards, and daily caps.

Knowledge points with progressive difficulty — structured as a staircase from simple to complex.

Current billing availability and the setup required before paid subscriptions can open.