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SKILL verified MIT Self-run

Qmt Bridge Return Analysis

skill-atorber-qmt-trading-skill-qmt-bridge-return-analysis · by atorber

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Install

$ agentstack add skill-atorber-qmt-trading-skill-qmt-bridge-return-analysis

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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How agent discovery & health will work →
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About

QMT Trading Skill · 累计涨幅与涨跌概率

> 实现状态:✅ return_probability_analysis.py 可用

目标

回答:

  1. 指定股票在 1、2、3、4、5、10、30 个交易日上的收盘累计涨幅(%)
  2. 基于 近 10 个交易日日 K 涨跌形态 + 更长历史回测,给出 下一交易日收涨的条件概率;样本不足时自动 缩短形态 / 放宽 1 位 / 小样本收缩估计
  3. 结合 连续多日成交量(相对 5 日均量、3 日量增、量价状态)评估涨跌概率(统计描述,非投资建议)

脚本

| 脚本 | 作用 | |------|------| | scripts/return_probability_analysis.py | --codes--holdings;缺 K 自动下载 |

# 当前持仓一键分析(需 API Key)
python skills/qmt-bridge-return-analysis/scripts/return_probability_analysis.py --holdings --host 127.0.0.1 --port 8080 --api-key YOUR_KEY

python skills/qmt-bridge-return-analysis/scripts/return_probability_analysis.py --codes 000001.SZ,600519.SH --host 127.0.0.1 --port 8080
python skills/qmt-bridge-return-analysis/scripts/return_probability_analysis.py \
  --codes 300394.SZ,688008.SH --json

| 参数 | 说明 | |------|------| | --codes | 逗号分隔股票代码(与 --holdings 二选一) | | --holdings | 从账户持仓读取标的;缺日 K 时自动 download_batch | | --download-start | 自动补 K 起始日(默认 20240101) | | --skip-download | 不自动下载日 K | | --count | 拉取日 K 根数(默认 150) | | --dividend-type | 复权:front / none / back 等 | | --pattern-len | 形态匹配长度(默认 9 日) | | --json | JSON 输出 | | --no-detail | 不展示近 10 日逐日表 | | --no-strategy | 不输出下一交易日策略与观察点 |

提示词示例(可复制)

优先引导 Agent 执行 skills/qmt-bridge-return-analysis/scripts/return_probability_analysis.py--holdings--codes)。

| 场景 | 提示词 | |------|--------| | 持仓一键(推荐) | 评估当前持仓的 1/5/10/30 日累计涨幅、量价涨跌概率,并总结明日操作策略与观察点 | | | 用 return-analysis skill 跑 --holdings,缺 K 线自动下载 | | 指定标的 | 分析 300394.SZ、688008.SH 的阶段涨幅和近 10 日上涨概率 | | | 这几只股票 1 日、5 日、30 日涨幅各多少,谁更强 | | 量价 | 结合成交量看持仓明日收涨概率和放量确认度 | | | 哪些持仓近 3 日量价形态偏强,历史次日统计如何 | | 形态 | 用 9 日 K 线形态统计下一日收涨概率,样本不够就缩短形态 | | 明日计划 | 根据持仓报告,给每只写明日观察点和一日策略(不荐股) | | | 组合层面:谁 30 日强、谁昨日回调大,明天优先盯什么 | | 机器可读 | 持仓涨幅概率分析,输出 JSON(加 --json) |

Agent 执行要点--holdings--host 127.0.0.1 与 API Key;.envQMT_BRIDGE_HOST=0.0.0.0 时客户端仍连 127.0.0.1

主要 API

| 方法 | 路径 | 说明 | |------|------|------| | GET | /api/market/market_data_ex | 日 K(period=1d) | | GET | /api/utility/batch_stock_name | 中文名称 |

计算说明

  • N 日累计涨幅close[-1] / close[-1-N] - 1(交易日收盘)
  • 近 10 日收涨占比:最近 10 个日收益率中收涨天数比例
  • 形态条件概率:取最近 pattern_len 日的涨跌方向序列匹配历史;样本不足时依次 缩短至 3 日 → 允许 1 位不匹配 → 向历史基准收缩(输出会标注 缩短形态/放宽1位/小样本收缩
  • 量价状态概率:近 3 日「涨/跌 + 放量/缩量/平量」组合在历史中的下一日收涨比例
  • 收涨放量→次日:历史「收涨且量比≥1.15(相对5日均量)」后次日收涨比例
  • 连增3日量→次日:连续 3 日成交量递增后次日收涨比例
  • 近10收涨放量占比:近 10 日收涨日中,成交量高于 5 日均量的天数占比(量能确认度)

规程

  1. 确认 Bridge 可用;--holdings 需配置 QMT_BRIDGE_API_KEY
  2. 持仓模式:读 query_positionsmarket_data_ex;不足则 download_batch 后重试
  3. 输出汇总表 + 分标的累计涨幅表 + 概率指标 + 下一交易日策略与观察点--no-strategy 可关闭)
  4. 只读,不下单;概率为历史统计,不构成预测或投资建议

安全

  • --codes 只读,默认无需 API Key;--holdings 需 API Key(读持仓)

参考

  • [qmt-bridge-market-watch](../qmt-bridge-market-watch/SKILL.md) · [qmt-bridge-sector-theme](../qmt-bridge-sector-theme/SKILL.md)
  • docs/rest-api.md

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.