By nagisanzenin
Learn any topic using first-principles curricula, generation-first Socratic tutoring, free-recall verification with receipts, and FSRS-scheduled spaced repetition. Also builds interactive HTML explorables and decomposes topics into concept DAGs.
Builds interactive HTML explorables for Engram threshold concepts under the binding Explorable Contract. Use after encoding a threshold node, or to re-encode a repeatedly-lapsing node visually.
Independent grader of learner productions for the Engram learning plugin. MUST BE USED for /learn verification and /review audits. Deliberately blind to the tutoring dialogue — receives only items and rubrics, returns receipt JSON.
Decomposes any topic into a first-principles concept DAG for the Engram learning plugin. Use when starting a new learning topic or restructuring one. Returns strict JSON for `engram.py add-topic`.
Learning telemetry, strategy, and schedule — retention stats, calibration, n-of-1 experiments, HTML dashboard. Use for "how am I doing", weekly check-ins, strategy questions, or adjusting how Engram teaches.
Learn any topic properly — first-principles curriculum, generation-first tutoring, verified free recall, FSRS scheduling. Use when the user wants to learn, understand, study, or continue studying something.
Clear due memory reviews with free recall — the two-minute habit that makes learning permanent. Use when reviews are due, or the user wants to review, practice, or "do my engram reviews".
Uses power tools
Uses Bash, Write, or Edit tools
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
claude plugin marketplace add nagisanzenin/engram
claude plugin install engram@engram
Then, inside Claude Code:
/learn kalman filters ← or music theory, or Rust lifetimes, or anything
That's the whole onboarding. No config, no account, no cards to write. Requires python3 (stock macOS/Linux one is fine — stdlib only).
On OpenAI Codex? Engram is an omni-repo — the same skills and engine run there too (
codex plugin marketplace add nagisanzenin/engram). See INSTALL-CODEX.md.
You already ask Claude to explain things. It explains beautifully. You nod, you feel smart, and ten days later it's gone — because a chat has no memory of you, no test of whether you really got it, and no plan for the forgetting that starts the moment you close the terminal.
Engram is what's missing around the explanation: a tutor that makes you do the thinking, an examiner that checks you actually got it, and a scheduler that brings each idea back right before your brain drops it.
| Engram is | Engram is not |
|---|---|
| a tutor that makes you produce answers before it explains | a chatbot that explains while you nod along |
| a memory system — every concept gets a future review date | notes and summaries you'll never reopen |
| an independent examiner that grades you blind, in writing | self-assessed "yeah, makes sense" |
| plain JSON files on your machine | a cloud service, account, or subscription |
Concretely, installing it gives you: three slash commands (/learn, /review, /coach), a quiet session hook that tells you when reviews are due (and says nothing otherwise), and a state folder at ~/.claude/learning/ that you own and can read.
recall
100% ─┐ just reading 100% ─┐ with engram
│\ │\ ●╌╌╌●╌╌╌╌╌●╌╌╌╌╌╌╌●╌╌
│ \ │ \ ╱ ╲╱ ╲╱
│ \__ │ ●──╱
│ \____ │
│ \_______ │ each ● = a 2–4 minute /review,
0% ─┴──────────────────── day 30 0% ─┴─ booked just before you'd forget
YOU ──→ /learn transformers
│
▼
┌────────────────────────────────────────────────────────────────┐
│ CURRICULUM ARCHITECT │
│ breaks the topic into a first-principles concept map: │
│ "what must be understood before what" — never chapter order. │
│ flags the few THRESHOLD concepts † that unlock everything. │
└────────────────────────────────────────────────────────────────┘
│
▼
┌────────────────────────────────────────────────────────────────┐
│ THE TUTOR (your normal Claude chat, under strict rules) │
│ │
│ per concept: open a question → you PREDICT → struggle a │
│ little (hints, not answers) → resolve → you EXPLAIN IT BACK │
│ │
│ threshold concepts get a generated interactive HTML │
│ explorable — sliders and prediction gates, not more text. │
└────────────────────────────────────────────────────────────────┘
│ your answers, verbatim (crash-safe stash on disk)
▼
┌────────────────────────────────────────────────────────────────┐
│ THE ASSESSOR (separate agent — grades blind) │
│ sees only the rubric and your words, never the lesson. │
│ every grade becomes a receipt on disk. no receipts, │
│ no mastery claim. │
└────────────────────────────────────────────────────────────────┘
│ receipts
▼
┌────────────────────────────────────────────────────────────────┐
│ THE SCHEDULER (engram.py — deterministic code, not vibes) │
│ FSRS-4.5 fits your personal forgetting curves and books │
│ each concept's next review just before you'd lose it. │
└────────────────────────────────────────────────────────────────┘
│
▼
npx claudepluginhub nagisanzenin/engram --plugin engramEnhances Claude Code from producing raw code into delivering production-ready systems. 14 specialized agents handle architecture, tested code, security audit, CI/CD, and documentation. Use for building apps/websites/services, adding features, hardening, deployment, testing, review, or architecture design.
Calibrated per-subagent reasoning effort: classify each subtask, dispatch it to the cheapest tier that still passes.
A roster of 60 fully-specified human voice profiles plus a deterministic AI-tell scanner. Write, humanize, audit, and mass-produce social posts that read as distinct, genuine people — verified by stylometry, not vibes.
A personal AI tutor based on Bloom's 2-sigma research: it generates a structured syllabus, teaches one adaptive lesson at a time, and tailors each next lesson to the learner's highlights and feedback. Bundles the bloom-tutor tutoring skill plus six learn-* learning-method skills.
Adaptive tutor skill with 10 teaching modes, active teaching tools, and a browser-based visual companion — runs code, creates exercises, generates interactive diagrams, quizzes, and walkthroughs. Makes Claude act as an interactive coach for learning any subject.
Interactive learning companion — creates personalized learning plans, quizzes with adaptive difficulty, and tracks progress across sessions
Agent skills that package evidence-backed pedagogical methodologies (explain-and-check, quiz-me, connect-to-what-you-know, ask-me-questions, learn-by-doing, linked-notes, flashcards) as workflows applied to code. The anti-cognitive-surrender layer: closes the comprehension gap that opens when an LLM has done the work on the human's behalf.
Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex and antigravity CLIs when installed) to get diverse perspectives on coding problems
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.