AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
Documentation for learn-content-engine
Translation pending
Developer toolsTypeScript · JavaScriptGitHub @astrapi69OnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
Framework-agnostic TypeScript engine that parses lesson content from pluggable sources into a canonical lesson object.
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
Framework-agnostic TypeScript engine that parses and validates lesson
content from pluggable sources into a canonical lesson object.
It takes raw content (a single-JSON lesson plus a manifest.yaml) and a set
context, and produces canonical lesson / set-entry objects. It contains no
network, storage, or UI code - you supply the bytes and keep fetch +
persistence. The bundled, strict JSON-Schema makes it a self-contained format
reference: you can author and validate lessons without the application the
format originated in (Adaptive Learner).
Tracks the lesson schema, currently v1.14.Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
Framework-agnostic TypeScript engine that parses and validates lesson
content from pluggable sources into a canonical lesson object.
It takes raw content (a single-JSON lesson plus a manifest.yaml) and a set
context, and produces canonical lesson / set-entry objects. It contains no
network, storage, or UI code - you supply the bytes and keep fetch +
persistence. The bundled, strict JSON-Schema makes it a self-contained format
reference: you can author and validate lessons without the application the
format originated in (Adaptive Learner).
Tracks the lesson schema, currently v1.14.Read the full README ↗