christina
Project Christina:自主认知放大器
[快速开始](#- 1-command-zero-friction-installation) • 架构 • MCP 工具 • CLI 参考 • 文档 • 贡献指南
🌟 执行摘要:消除上下文腐化
现代 AI 编码智能体在大规模代码库($10\text{M}+$ tokens)上失败,原因不在于推理能力,而在于Context Rot(上下文腐化):注意力分散、未索引的提示词污染、上下文清空后架构约束丢失,以及不协调的集群冲突。
Project Christina 通过一套集成的高性能认知三位一体方案来解决这些问题:
RLM(递归语言模型——上下文即变量):将大规模代码库移出对话提示词,放入沙箱化的堆变量(
context)中。智能体执行有界子查询($D \le 2, N \le 20$)和带自动回滚的事务式写时复制(CoW)Python 控制循环。Graphify(确定性 CPG 与 AST 雷达):构建内存 SQLite3 WAL 调用图,实现 亚 0.3ms 递归 CTE 查询、传递性爆炸半径分析和中心性极高的 Node 节点排名,带来 71.5x 的 token 发现量缩减。
OKF(持久语义记忆与认知进化):亚微秒级正则 frontmatter 解析($6.72\ \mu\text{s}$/doc)、正式 AGM 信念修正、艾宾浩斯遗忘曲线,以及带 $\le 400$-token 自动压缩后记忆恢复锚点的 Mark-and-Sweep 语义垃圾回收。
跨项目认知蒸馏:将专有代码匿名化为数学原型,具备严格的零信息泄漏不变量($\mathcal{I} = 0$)、多进制 Shannon 熵秘密清洗机制,以及跨代码库的贝叶斯不变量聚合。
集群并发控制:使用 Kung-Robinson 乐观并发控制(OCC)、Tree-CRDT 三方 AST 合并以及 Linda 元组空间黑板机制,实现去中心化多智能体执行。
🏛️ 三支柱认知架构
┌─────────────────────────────────────────┐
│ SUPERVISOR / AGENT │
│ (Antigravity / OpenCode / Claude / AI) │
└────────────────────┬────────────────────┘
│ JSON-RPC 2.0 (stdio)
▼
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ PROJECT CHRISTINA FAST-MCP GATEWAY │
├──────────────────────────────────────┬────────────────────────────────────┬───────────────────────────────────────┤
│ PILLAR 1: RLM ENGINE │ PILLAR 2: GRAPHIFY CPG │ PILLAR 3: OKF MEMORY │
│ (Context as Variable) │ (AST Code Radar) │ (Semantic Evolution) │
├──────────────────────────────────────┼────────────────────────────────────┼───────────────────────────────────────┤
│ • Out-of-core Heap Variables │ • In-Memory SQLite3 WAL Graph │ • Sub-microsecond OKF Regex Parser │
│ • Transactional CoW Rollback │ • Sub-0.3ms Transitive Blast Query │ • Formal AGM Belief Revision │
│ • 3-Phase EGRI Invariant Linter │ • Composite God-Node Centrality │ • Ebbinghaus Forgetting & GC │
│ • Dynamic Governor (D<=2, N<=20) │ • Circular Dependency & Wave Sort │ • Symbol-to-ADR Constraints │
└──────────────────────────────────────┴────────────────────────────────────┴───────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ DECENTRALIZED SWARM & DISTILLERY │
├───────────────────────────────────────────────────────────────────┬───────────────────────────────────────────────┤
│ SWARM CONCURRENCY BLACKBOARD │ GLOBAL EPISTEMIC DISTILLERY │
├───────────────────────────────────────────────────────────────────┼───────────────────────────────────────────────┤
│ • Kung-Robinson Optimistic Concurrency Control (OCC) │ • Zero-Information Leakage (I = 0) │
│ • Semantic Tree-CRDT 3-Way AST Merge Resolution │ • Multi-Base Shannon Entropy Secret Redaction │
│ • Linda Tuple Space (`out`, `rd`, `in`, `eval`, `digest`) │ • Bayesian Invariant Distillation (0700 Fence)│
└───────────────────────────────────────────────────────────────────┴───────────────────────────────────────────────┘Mermaid 流程图
flowchart TD
Host[Host Agent Context] -->|JSON-RPC 2.0 stdio| MCP[Christina FastMCP Server]
subgraph Trinity["Autonomous Cognitive Trinity"]
MCP -->|cpg_query| CPG[Graphify CPG Radar<br/><i>sub-0.3ms SQLite WAL</i>]
MCP -->|rlm_execute| RLM[RLM Sandbox<br/><i>Transactional CoW REPL</i>]
MCP -->|memory_evolve| OKF[OKF Semantic Memory<br/><i>AGM Revision & Epistemic GC</i>]
end
subgraph SwarmDistill["Swarm & Cross-Project Substrate"]
MCP -->|swarm_blackboard| OCC[Swarm Concurrency<br/><i>Kung-Robinson OCC + Tree-CRDT</i>]
OKF -->|distill_global| Distill[Global Epistemic Distillery<br/><i>Anonymized Archetypes (I=0)</i>]
end
CPG -.->|Blast Radius & Waves| OCC
RLM -.->|Isolated Sub-Calls| Host
OKF -.->|ADR Anchor <=400 Tokens| Host🚀 一条命令,零摩擦安装
Christina 可在数秒内完成安装,无需后台守护进程、本地编译或 root 权限:
cd christina
./install.sh自动化诊断预检
./install.sh doctor================================================================
Christina Cognitive Amplifier Diagnostics (v1.0.0)
================================================================
✓ Python Version: 3.11+ (Requirement satisfied)
✓ SQLite3 in-memory WAL Engine: Ready
✓ OKF Semantic Memory Engine: Ready
✓ Google Antigravity Plugin: Registered
✓ OpenCode Plugin: Registered
✓ Global memory directory: ~/.config/christina/global_memory (0700 fenced)
================================================================
✅ All systems functional.运行完整测试套件(62/62 通过,耗时小于 <1.2s)
./install.sh test
# Or with pytest directly:
pytest tests/ -v🛠️ 标准 FastMCP 工具矩阵
Christina 提供 4 个统一 JSON-RPC 2.0 stdio 工具,兼容任何 MCP 主机:
工具 | 类别 | 关键能力与模式 | 性能上界 |
| AST 代码雷达 |
| 内存遍历 <0.3ms |
| 沙箱化执行 | 子智能体 MapReduce、事务式 CoW REPL、三阶段 EGRI linting 检查、计算资源抑制器目标 | 递归边界 $D \le 2, N \le 20$ |
| 语义记忆 |
| $6.72\ \mu\text{s}$/文档解析 |
| 集群并发控制 |
| 无锁乐观并发验证验证 |
MCP 工具调用
1. 爆炸半径分析(cpg_query)
{
"name": "cpg_query",
"arguments": {
"symbol": "PaymentGateway",
"mode": "blast_radius",
"depth": 3
}
}2. 事务式子查询执行(rlm_execute)
{
"name": "rlm_execute",
"arguments": {
"query": "Audit error recovery handling in database connection pool",
"scope_paths": ["src/db/", "src/pools/"]
}
}3. 带符号约束的语义记忆搜索(memory_evolve)
{
"name": "memory_evolve",
"arguments": {
"action": "search",
"query": "zero-trust authentication policy",
"linked_symbols": ["AuthMiddleware"]
}
}4. 集群 OCC 冲突校验(swarm_blackboard)
{
"name": "swarm_blackboard",
"arguments": {
"action": "occ_validate",
"worker_id": "worker_security_audit",
"read_version": 4,
"read_set": ["AuthMiddleware", "SessionToken"],
"write_set": ["AuthMiddleware"]
}
}⚡ CLI 快速参考
# 1. Scan codebase and index AST knowledge graph into in-memory SQLite3 WAL
python3 -m christina.cli scan .
# 2. Calculate static blast radius for a target symbol
python3 -m christina.cli blast AuthService --depth 3
# 3. List top God Nodes ranked by composite degree centrality
python3 -m christina.cli god-nodes --limit 10
# 4. Search OKF institutional memory, ADRs, and symbol constraints
python3 -m christina.cli memory "connection pool timeout" --symbol DatabasePool
# 5. Run FastMCP JSON-RPC 2.0 stdio server
python3 -m christina.cli serve
# 6. Execute system diagnostics
python3 -m christina.cli doctor🔌 多主机兼容与配置
1. Google Antigravity CLI(agy)
自动符号链接到 ~/.gemini/antigravity-cli/plugins/christina,并注册到 ~/.gemini/antigravity-cli/mcp_config.json。
2. OpenCode
自动注册到 ~/.config/opencode/plugins/christina 以及 ~/.config/opencode/opencode.json。
3. Claude Desktop
自动配置到 ~/.claude/claude_desktop_config.json(macOS 上为 ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"christina": {
"command": "python3",
"args": ["-m", "christina.bridge.mcp_server"],
"env": {
"PYTHONPATH": "/path/to/christina"
}
}
}
}4. OpenAI Codex CLI
自动注册到 ~/.config/codex/config.json。
🪮 Ponytail Ultra:零依赖保证
Project Christina 严格遵循 Ponytail Ultra 规范设计:
零外部运行时依赖:仅使用标准 Python 库(
ast,sqlite3,re,json,hashlib,fcntl,math,pathlib,typing)。零重型守护进程:不依赖 Docker、Neo4j、ChromaDB 或 Redis。内存 SQLite3 WAL 和 POSIX 文件锁可提供亚毫秒级执行,空闲后台内存占用为 $0\text{MB}$。
严格代码精简:每个模块精简(不足 250 行代码)、内聚且自包含。
📚 文档与指南
文档 | 描述 |
分步安装、验证和首个 Agent 工作流。 | |
渐进式揭示的技能定义( | |
Ponytail Ultra 开发规范、Nix 环境、测试套件和 ADR 工作流说明。 | |
零信息泄漏不变量($\mathcal{I} = 0$)、Shannon 熵敏感信息净化与隔离机制。 | |
详细的发布说明与版本历史。 |
📜 许可证
Project Christina 以开源 MIT 许可证 形式分发。
© 2026 Christina Engineering Swarm 与贡献者。
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