- Generate full AI-consumable docs (docs/ai/): system overview, architecture, module cheatsheet, API contracts, data model, build guide, decision log, glossary, and open questions (deep tier coverage) - Add PROBLEM_REPORT.md: categorized bug/risk summary - Add DETAILED_CODE_REVIEW.md: full line-by-line review of all 15 backend files, documenting 4 fatal issues, 5 critical deployment bugs, 4 security vulnerabilities, and 6 architecture defects with prioritized fix plan
3.4 KiB
3.4 KiB
| generated_by | version | created | last_updated | source_commit | coverage |
|---|---|---|---|---|---|
| repo-insight | 1 | 2026-03-03 | 2026-03-03 | 0d9dffa |
deep |
Arbitrage Engine — AI Documentation Index
Project: arbitrage-engine
Summary: Full-stack crypto perpetual futures funding-rate arbitrage monitoring and V5.x CVD/ATR-based short-term trading signal engine. Python/FastAPI backend + Next.js frontend + PostgreSQL + Binance USDC-M Futures.
Generated Documents
| File | Description |
|---|---|
| 00-system-overview.md | Project purpose, tech stack, repo layout, entry points, environment variables |
| 01-architecture-map.md | Multi-process architecture, component diagram, signal pipeline data flow, risk guard rules, frontend polling |
| 02-module-cheatsheet.md | Module-by-module index: role, public interfaces, dependencies for all 20 backend + 15 frontend files |
| 03-api-contracts.md | All REST endpoints, auth flows, request/response shapes, error conventions |
| 04-data-model.md | All PostgreSQL tables, columns, partitioning strategy, storage design decisions |
| 05-build-run-test.md | 构建/运行/部署命令,环境变量,PM2 配置,回测和模拟盘操作 |
| 06-decision-log.md | 9 项关键技术决策:PG 消息总线、循环间隔、双写、分区、自研 JWT 等 |
| 07-glossary.md | 交易术语(CVD/ATR/R/tier)+ 工程术语(paper trading/warmup/circuit break) |
| 99-open-questions.md | 11 个未解决问题:users 表双定义冲突、依赖不完整、硬编码密码、无测试等 |
Recommended Reading Order
- Start here:
00-system-overview.md— 了解项目定位和结构。 - Architecture:
01-architecture-map.md— 理解 7+ 进程的交互方式。 - Data:
04-data-model.md— 任何 DB 相关工作的必读;注意时间戳格式不统一问题。 - API:
03-api-contracts.md— 前端开发或 API 对接时参考。 - Module detail:
02-module-cheatsheet.md— 修改特定文件前的参考。 - Ops:
05-build-run-test.md— 部署和运维操作。 - Concepts:
07-glossary.md— 不熟悉量化术语时查阅。 - Risks:
99-open-questions.md— 开始开发前必读,了解已知风险点。
Coverage Tier
Deep — 包含完整的模块签名读取、核心业务模块深度阅读(signal_engine 全文、evaluate_signal 评分逻辑、backtest.py)、构建运行指南、决策日志、术语表和开放问题。
Key Facts for AI Agents
- Signal engine is the core:
backend/signal_engine.py— change with care; affects all trading modes. - Strategy tuning via JSON: modify
backend/strategies/v51_baseline.jsonorv52_8signals.jsonto change signal weights/thresholds without code changes. - No ORM: raw SQL via
asyncpg/psycopg2; schema indb.py:SCHEMA_SQL. - Auth is custom JWT: no third-party auth library; hand-rolled HMAC-SHA256 in
auth.py. TRADE_ENV=testnetdefault: production use requires explicit env override + strong JWT_SECRET.- Dual timestamp formats:
ts= Unix seconds,time_ms/entry_ts/timestamp_ms= Unix milliseconds — do not confuse.
Generation Timestamp
2026-03-03T00:00:00 (UTC)