feat: 新增项目 CryptoAnalysisAgent - 加密货币多维分析智能体#638
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pr名称，内容之类的要按照规范填写哈 |
性能优化: - 新增 market_data 共享数据访问层: Session 连接复用 + TTL 缓存 + 自动重试， 一轮分析的 HTTP 请求从约 8 次降至约 3 次 - Coordinator 新增 run_full_analysis 工具，线程池并行运行三位分析师， 综合分析耗时从三者之和降为最慢的一个 - EMA/MACD/支撑阻力计算向量化，MACD 一次计算完整序列消除重复全量计算 Agent 考核体系 (src/evaluation/): - report_checks: 结构合规率 / 条件化建议 / 数据真实性(数字溯源) 规则化考核 - telemetry: 端到端延迟、工具调用次数、HTTP 请求与缓存命中埋点 - judge: LLM-as-Judge 五维语义质量评审 - 四个 Agent prompt 增加反幻觉约束 (数字必须来自工具返回) 信号留痕 (signal_ledger): - 每次分析自动归档方向判断与信号时刻价格 (outputs/signals.jsonl) - 到期后用 Binance 历史 K 线核算 24h/7d 对错，输出分周期/分币种胜率 notebook 新增 Part 4.5 (考核演示) 与 Part 4.6 (信号留痕)，README 同步更新 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- 一条命令完成: 分析 → 质量门禁 → 报告归档 → 信号留痕 - 质量门禁有拦截力: 结构/条件化检查未通过的报告标记 NOT_PASSED， 不归档信号，避免污染对外胜率记录 - --settle 模式核算到期信号并输出历史胜率 - --judge 可选执行 LLM Judge 语义评审 - 懒加载依赖，配合 crontab 即可实现每日定时报告 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- create_coordinator 新增 sub_llm 参数: 子 Agent 数据整理用小模型， 强模型留给 Coordinator 综合判断 - 支持 LLM_SUB_MODEL_ID 环境变量零代码启用，创建失败自动回退主模型 - .env.example 与 README 同步说明 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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pr名称应该是[毕业设计] xxx（英文项目名）-xxx（中文）的格式，然后可以让claude 把 commit合并为一个 |
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项目介绍
Co-creation-projects/gpteth-CryptoAnalysisAgent— 基于 HelloAgents 框架构建的多 Agent 协作加密货币分析系统，融合技术分析、链上数据、市场情绪三维视角，生成交叉验证的结构化分析报告。设计理念来源于 NOFXi 交易系统的实战经验（Skill-first、条件化建议、风险优先）。核心内容
多 Agent 架构
run_full_analysis工具用线程池并行运行三位分析师，综合分析耗时从三者之和降为最慢的一个性能设计
market_data共享数据访问层：Session 连接复用 + TTL 缓存 + 自动重试，一轮分析的 HTTP 请求从约 8 次降至约 3 次Agent 考核体系（对应第十二章评估框架，
src/evaluation/）信号留痕与历史胜率
运行方式
main.ipynb完整教学演示（含 Part 4.5 考核、Part 4.6 信号留痕）analyze.pyCLI：分析 → 质量门禁 → 报告归档 → 信号留痕一条命令，配合 crontab 实现每日定时报告测试情况
🤖 Generated with Claude Code