0xwilliamortiz
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ponytail-improved
Ponytail is a plugin for AI coding agents that enforces a disciplined ladder of reuse before writing code, reducing code volume by roughly 54% while preserving safety.
AI 仓库情报摘要
FR-AI / ANALYSIS为什么值得关注
其显著之处在于将严格的认知科学（生成效应、FSRS 调度、盲评）融入编码助手的流程中，拥有经过全面审计的评分器（从未出现分数膨胀，0/258），且数据完全本地化。
适合谁使用
- 使用 AI 编码助手并希望记住技术概念的开发者
- 自学 STEM、乐理或其他结构化主题的个体
- 对基于证据的 AI 辅导和记忆保持感兴趣的教育者和研究者
- Claude Code、OpenAI Codex 或其他支持平台的用户
典型使用场景
- 在编码过程中学习新主题（如卡尔曼滤波器、Rust 生命周期）
- 每天 2–4 分钟的快速复习以巩固所学内容
- 每周教练功能查看记忆统计、校准和仪表盘
- 可选地导出匿名学习数据以支持社区科学（需明确同意）
项目优势
- 基于证据：采用生成效应、间隔练习、FSRS-4.5 调度和盲评
- 多平台：支持 Claude Code、OpenAI Codex、OpenCode、Hermes Agent、Antigravity、OpenClaw
- 隐私优先：100% 本地运行（无网络代码，经构建测试验证），状态文件归用户所有
- 评分器经过审计：258 项盲评中无一项分数膨胀；金集公开可审计
使用前须知
- 需要 Python3（仅标准库，macOS/Linux 自带的即可）
- 学习会话可能需要 5–60 分钟（由用户控制强度）
- 部分平台集成存在小缺陷（例如 Antigravity 的复习提醒未移植，OpenClaw 需要配置标志）
README 快速开始
Your AI can explain anything. Engram makes sure you still know it next month.
The mix-up worth clearing first: Engram is not an agent-memory plugin. It doesn't give your agent persistent memory, context, or knowledge of your codebase — memory MCPs and context tools do that, for the agent. Engram points the other way: it's a learning system for the human. Your agent becomes a tutor that makes you do the thinking, a blind examiner that checks you actually got it, and a scheduler that brings each idea back right before your brain drops it. The agent doesn't get smarter. You do — measurably, with receipts.
Born as a Claude Code plugin; the same skills and engine now run on six agentic platforms — including, as of v1.0.8, one that puts the tutor in your chat app:
claude plugin marketplace add nagisanzenin/engram
claude plugin install engram@engram
| Platform | Install | Then |
|---|---|---|
| Claude Code (born here) | the two commands above | /learn /review /coach |
| OpenAI Codex | codex plugin marketplace add nagisanzenin/engram then codex plugin add engram@engram → INSTALL-CODEX.md | $learn $review $coach |
| OpenCode | "plugin": ["opencode-engram-learning"] in opencode.json (npm) | /learn /review /coach |
| Hermes Agent | clone + skills.external_dirs → INSTALL-HERMES.md — verified live on v0.18.2 | /skill learn (or /study) /review /coach |
| Google Antigravity | agy plugin install https://github.com/nagisanzenin/engram | /learn /review /coach |
| OpenClaw | openclaw plugins install engram --marketplace nagisanzenin/engram → INSTALL-OPENCLAW.md — verified on 2026.7.1-2 | /learn /review /coach |
OpenCode: opencode.json is read globally (~/.config/opencode/opencode.json) or per-project; pin to source instead of npm with "plugin": ["git+https://github.com/nagisanzenin/engram.git"].
Antigravity: The due-review session nudge isn't ported yet, and the architect and smith subagents are currently dropped by AG 1.1.4's strict installer. Everything else works the same.
OpenClaw: the nudge needs openclaw config set hooks.internal.enabled true (OpenClaw ignores plugin hooks until internal hooks are switched on), and it fires on `/new
项目描述
Evidence-based learning engine for Claude Code — first-principles curricula, free-recall verification with receipts, FSRS-scheduled memory, and explorable artifacts. Learn anything; keep it.
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