engram
Evidence-based learning engine — first-principles curricula, free-recall verification with receipts, FSRS-scheduled memory, and explorable artifacts. Learn anything; keep it.
- 1.5k stars
- 107 forks
- 4 open issues
- Language: Python
- License: MIT
- updated
Install
/plugin marketplace add nagisanzenin/engram
/plugin install engram- Inside Claude Code, add the marketplace and install the plugin with the commands above.
- Follow any post-install configuration from the README.
- Restart the session if commands or hooks do not show up immediately.
6 items in this repository
Learning telemetry, strategy, and schedule — retention stats, calibration, grader audit, n-of-1 experiments, HTML dashboard. Use for "how am I doing", weekly check-ins, strategy questions, auditing the grader, or adjusting how Engram teaches.
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`.
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".
Plugins overview
What people ask about engram
What is nagisanzenin/engram?
nagisanzenin/engram is plugins for the Claude AI ecosystem. Evidence-based learning engine — first-principles curricula, free-recall verification with receipts, FSRS-scheduled memory, and explorable artifacts. Learn anything; keep it. It has 1.5k GitHub stars and its last recorded update is dated 2026-08-27.
How do I install engram?
You can install engram by cloning the repository (https://github.com/nagisanzenin/engram) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is nagisanzenin/engram safe to use?
Our security agent has analyzed nagisanzenin/engram and assigned a Trust Score of 92/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains nagisanzenin/engram?
nagisanzenin/engram is maintained by nagisanzenin. The last recorded GitHub activity is dated 2026-08-27, with 4 open issues.
Are there alternatives to engram?
Yes. On ClaudeWave you can browse similar plugins at /categories/plugins, sorted by popularity or recent activity.