learning-science

Evidence-based learning engine — first-principles curricula, free-recall verification with receipts, FSRS-scheduled memory, and explorable artifacts. Learn anything; keep it.

165 evidence-grounded AI skills for teachers, school leaders and EdTech builders—pedagogy, learning science, curriculum, assessment and regeneration. Claude, Codex and Hermes.

🌳 AI-Powered Skill Tree for Lifelong Human Learning. 30+ skills from K-12 to career & social intelligence, built on cognitive science. | 人类养成记：AI 驱动的终身学习技能树

The data layer for smarter educational AI. Integrate trusted instructional content and research directly into your AI-powered tools — improving precision, relevance, and instructional alignment.

Evaluation for AI outputs against trusted educational rubrics. Measure and improve content quality with research-backed rubrics — ensuring rigor, reliability, and alignment to classroom needs.

Universal AI agent skill that turns any material into learning-science-based self-study courses with retrieval practice, spaced repetition, and tutor mode.

🎓 A teaching skill for AI coding agents — teaches from your level, then verifies real learning by restatement. Adapted from Matt Pocock's teach (MIT).

AI-agnostic skill for writing BrainLifts: structured context docs that turn research into DOK knowledge trees, insights, and spiky POVs.

把硬核长内容拆成obsidian的思维导图 · 通用 AI 提示词框架(Claude/ChatGPT/Gemini)

Research-backed concepts for educators teaching AI literacy. How to preserve human thinking, judgment, and agency while using AI productively.

Stay sharp while AI does the work: a Claude Code plugin for judgment, understanding and transfer — one-way door gates, change briefs, and lessons that come back when you need them.

Local-first mastery tutor for AI agents with guided HTML lessons, hands-on practice, transfer checks, spaced review, and learner-owned progress.

Distraction-free AI learning. Stay with one concept at a time using clear explanations, useful analogies, visual structure, and active recall.

Glossy interactive React lab for human and agent memory systems.

An Intelligent Lecturing Assistant

An Agent Skill for AI teaching that reasons about the learner's current understanding and chooses the next teaching move, grounded in cognitive and learning science.

Evidence-driven Agent Skill for systematic learning: retrieval, discrimination, transfer, performance, and long-term continuity.

Agent Skill that quizzes you on its own answers — one multiple-choice question after each substantive reply, graded and explained. Ambient retrieval practice against AI deskilling. Instruction-only: no scripts, no network, no data sent. MIT.

伏羲框架 · 万物皆可学 — Everything Can Be Learned｜十阶时间线 × 证据分级 × 开源工具链

Eleven skill dimensions per word, FSRS-6 scheduling per skill, and no mastery until you can produce the word in writing. Each mistake is sorted into one of seven error categories, and no word enters practice before it's taught. Runs in the browser from one HTML file, with no server, no account and no network requests