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Revise README for improved clarity and bilingual support
Updated README to enhance clarity and structure, adding sections in both English and Chinese.
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README.md

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# CodeCart
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CodeCart: A portable, single-file cognitive memory cartridge for AI collaboration. End long-context pollution and save tokens with DSL-driven knowledge graphs. / 专为 AI 协作设计的便携单文件认知记忆卡带,终结上下文污染并极致节省 Token。
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🇺🇸 English Version
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CodeCart: The Single-File Cognitive Memory Cartridge
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CodeCart is a portable, evolvable, and token-efficient knowledge graph stored in a single HTML file. It solves the "Long Context Inflation" and "Memory Pollution" issues in AI collaboration.
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🌟 Key Features
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Dual-Drive I/O: High-efficiency DSL instructions instead of bulky JSON.
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4D Timeline: Temporal playback to revisit historical decision points.
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Lens System: Multi-perspective projection (Engineering, Patent, Security, etc.).
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Physical Portability: Single-file HTML, zero-dependency, U-disk ready.
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🛠 How to Use
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Sync: Click "Copy for AI" to get a compressed Markdown context.
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Chat: Paste it to AI. AI replies with DSL commands (e.g., +CLAIM).
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Execute: Paste DSL back into the console and click "Execute".
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🇨🇳 中文说明
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CodeCart:单文件认知记忆卡带
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CodeCart 是一款便携、可演化且极致节省 Token 的认知图谱容器,封装于单个 HTML 文件中。它旨在解决 AI 协作中常见的“长上下文膨胀”与“记忆污染”痛点。
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🌟 核心特性
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非对称双擎 I/O:使用极简 DSL 指令取代臃肿的 JSON,节省 90% 输出 Token。
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4D 时间轴:状态时空切片,支持回溯任何历史决策现场。
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多维透镜:根据任务切换视角(工程、专利、安全等),精准过滤噪声。
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物理级便携:单文件零依赖,优盘即插即用,数据主权完全掌控。
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🛠 使用步骤
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同步:点击“复制给 AI”获取压缩后的 Markdown 上下文。
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对话:贴给 AI。AI 会输出 DSL 指令(如 +CLAIM)。
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回写:将指令贴回 CodeCart 控制台并点击“执行”。
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# CodeCart: The Cognitive Memory Cartridge for Human-AI Collaboration
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# CodeCart:人机协作认知记忆卡带
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CodeCart is a portable, single-file cognitive memory cartridge designed to end "AI Memory Pollution." It collapses thousands of words into structured logic nodes using a robust DSL engine.
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CodeCart 是一款专为终结“AI 记忆污染”而生的单文件认知图谱容器。它通过强大的 DSL 引擎,将万字长谈坍缩为结构化的认知节点。
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---
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## 🚀 快速上手指南 / Quick Start Guide
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### 第一步:开启认知白板 / Step 1: Initialize
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* **🆕 New Cartridge**: Click left-bottom button to clear all nodes.
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* **🆕 新建卡带**:点击左下角按钮,抹除所有节点,开启纯净画布。
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* **⚓ Set Anchors**: In the console, enter your hard constraints.
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* **⚓ 设定锚点**:在控制台输入物理级红线。
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- *Example:* `+ANCHOR("Budget limit: $1000")` / `+ANCHOR("预算限额 1000 元")`
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### 第二步:认知同步循环 / Step 2: The Cognitive Loop
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1. **📋 Copy for AI**: Click the button to get a compressed Markdown context.
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1. **📋 复制给 AI**:点击按钮,系统自动将当前逻辑状态压缩为 Markdown。
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2. **💬 Chat with AI**: Paste the text to any AI (Gemini, Perplexity, Grok).
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2. **💬 对话 AI**:将文本贴给任意 AI,并要求其以 DSL 格式回答。
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3. **⚡ Get & Exec**: Copy the DSL commands from AI, paste back to console, and click **Execute**.
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3. **⚡ 执行指令**:复制 AI 回复的 DSL 指令,贴回控制台点击“执行”,见证节点涌现。
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---
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## 🧠 高阶方案:安插文档与跨模型协作 / Advanced Workflows
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### 方案 A:认知坍缩(安插长文档/对话) / Scenario A: Cognitive Collapse
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If you have long PDF documents or 100+ chat logs, do not paste them directly to all AIs.
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如果您有长篇 PDF 或上百轮聊天记录,不要直接发给所有 AI。
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1. **Feeding**: Upload document to AI A (e.g., Claude/Gemini).
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1. **喂料**:将文档发给 AI A。
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2. **Shrinking**: Ask AI A to "Collapse the core logic into 3-5 CodeCart `+CLAIM` commands."
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2. **坍缩**:要求 AI A “将核心逻辑坍缩为 3-5 条 CodeCart `+CLAIM` 指令”。
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3. **Injecting**: Paste these commands into CodeCart.
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3. **注入**:将指令贴入 CodeCart。这样,复杂的文档就变成了可参与讨论的结构化节点。
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### 方案 B:跨模型逻辑接力 / Scenario B: Cross-Model Relay
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1. **AI A (Strategist)**: Ask Perplexity to propose a solution. Execute its `+CLAIM`.
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1. **AI A(战略家)**:让 Perplexity 提出方案,执行其 `+CLAIM`
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2. **AI B (Critic)**: Sync to Grok and ask: "Find logic holes in AI A's claim and optimize."
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2. **AI B(批判家)**:同步上下文给 Grok 并问:“找出 AI A 的逻辑漏洞并进行优化。”
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3. **Evolution**: AI B will output `>SUPERSEDE` to refine the knowledge graph.
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3. **演化**:AI B 会输出 `>SUPERSEDE` 指令,看图谱如何从旧逻辑中进化。
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---
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## 🤖 针对 API 用户与 Agent 协议 / For API & Agent Users
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If you are an API developer, inject this into your **System Prompt**:
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如果您是 API 开发者,请将此段加入您的**系统提示词**
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> "You are an expert cognitive architect. Refer to the CodeCart Context. Your output MUST conclude with DSL:
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> - `+CLAIM(ID, 'Statement')` for new logic.
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> - `>SUPERSEDE(old_id, new_id, 'Reason')` for updates.
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> - No explanations. Just the logic commit."
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---
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## 🛠 指令集参考 / DSL Syntax Reference
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| Command 指令 | Effect 作用 | Example 示例 |
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| :--- | :--- | :--- |
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| **+CLAIM** | Add new knowledge 新增节点 | `+CLAIM(ent_01, "方案 A 可行")` |
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| **>SUPERSEDE** | Refute/Update 替代旧逻辑 | `>SUPERSEDE(clm_01, clm_02, "发现漏洞")` |
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| **+ANCHOR** | Hard constraint 物理红线 | `+ANCHOR("所有代码须使用 Python 3.10")` |
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---
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## 🌍 全球化适用 / Global Design
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* **Partitioned UI**: Shades of gray distinguish sidebar, canvas, and console.
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* **分区 UI**:通过不同深浅的灰色区分边栏、画布与控制台,减少视觉疲劳。
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* **Micro-Precision Timeline**: Backtrack through decisions second-by-second.
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* **高精度时间轴**:支持分秒级回溯,即使是连续快速操作也能精准还原。
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* **Data Sovereignty**: 100% Offline. Your logic never leaves your local file.
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* **数据主权**:100% 离线,您的认知逻辑永远不会离开本地文件。
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---
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Created by **AgentLex**. Open Source under MIT License.

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