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qmt-bridge-kline-backfill

校验近N个交易日两市成交额（上证+深证）是否可用于复盘。默认仅用 get_full_tick 写当日与本地日缓存，不拉历史 K 线。用户提到补齐K线、近3日量能缺失、复盘前校验时使用。

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Prix non confirmé★ 24 Stars GitHubRegistre mis à jour · 9 oct. 2026agent-skill

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QMT Trading Skill · 近3日量能校验

实现状态：✅ index_turnover_recent.py · backfill_recent_index_kline.py
共享逻辑：_shared/market_turnover_util.py

目标

在执行复盘前，校验近 N 日（默认 3）两市成交额是否齐全：

上证指数：000001.SH
深市指数：399106.SZ（tick 缺 amount 时回退 399001.SZ）

官方推荐 vs 本项目策略

迅投知识库（指数数据）：

场景	官方 API	本项目复盘热路径
当日成交额	`get_full_tick` → `amount`	✅ `GET /api/market/full_tick`
历史指数日 K	`download_history_data` + `get_market_data_ex`	❌ 禁用（易 BSON 崩溃）
历史缺口	需本地已下载数据	✅ `reports/market_turnover_daily.json` 每日 tick 累积

复盘/校验默认不调用 download_batch、get_local_data、get_market_data_ex、get_market_data。

可选 --try-history：先 download_batch 指数日线，再 get_market_data 子进程补历史并写入缓存（QMT 异常时慎用）。

推荐补齐近 3 日缺口（历史缺失时）：

# 1. 下载指数日线（仅 3 只，勿全市场）
python -c "
from datetime import date, timedelta
import sys; sys.path.insert(0,'skills/_shared')
from common import load_env_files, make_client
import argparse
load_env_files()
c,_=make_client(argparse.Namespace(host='127.0.0.1',port=8080,api_key='test-auto',account_id=None),False)
e=date.today().strftime('%Y%m%d'); s=(date.today()-timedelta(days=12)).strftime('%Y%m%d')
print(c.download_batch(['000001.SH','399106.SZ','399001.SZ'], period='1d', start_time=s, end_time=e))
"

# 2. 读 amount 写入缓存并展示明细
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --host 127.0.0.1 --port 8080 --try-history

脚本

# 查看近3日上证+深证成交额明细（亿元）
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --host 127.0.0.1 --port 8080

# 查看近3日成交额明细；历史缺口加 --try-history
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --host 127.0.0.1 --port 8080

# 可选：尝试从本地 K 线补历史（慎用，优先用上一条）
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --try-history --host 127.0.0.1 --port 8080

# 兼容旧入口（同上逻辑）
python skills/qmt-bridge-kline-backfill/scripts/backfill_recent_index_kline.py --json

参数

参数	说明
`--days`	需要覆盖的最近交易日数量（默认 3）
`--try-history`	可选尝试 `get_market_data` 补历史（默认关闭）
`--json`	输出机器可读结果

输出说明

ok=true：近 N 个交易日缓存/tick 均有沪+深成交额
ok=false：列出缺失交易日；连续多日收盘复盘会自动写入缓存
method：默认 full_tick+cache

排障

当日 tick 失败 → 检查 QMT 登录与行情
历史不足 → 正常（需多日累积）；勿反复跑 --try-history
BSON / 服务无响应 → 重启 QMT 客户端，再重启 Bridge

Voir la source ↗

Métadonnées du fichier

name: qmt-bridge-kline-backfill
description: >-
  校验近N个交易日两市成交额（上证+深证）是否可用于复盘。默认仅用 get_full_tick 写当日
  与本地日缓存，不拉历史 K 线。用户提到补齐K线、近3日量能缺失、复盘前校验时使用。

Voir le texte original

---
name: qmt-bridge-kline-backfill
description: >-
  校验近N个交易日两市成交额（上证+深证）是否可用于复盘。默认仅用 get_full_tick 写当日
  与本地日缓存，不拉历史 K 线。用户提到补齐K线、近3日量能缺失、复盘前校验时使用。
---

# QMT Trading Skill · 近3日量能校验

> **实现状态**：✅ `index_turnover_recent.py` · `backfill_recent_index_kline.py`  
> 共享逻辑：`_shared/market_turnover_util.py`

## 目标

在执行复盘前，校验近 N 日（默认 3）两市成交额是否齐全：

- 上证指数：`000001.SH`
- 深市指数：`399106.SZ`（tick 缺 amount 时回退 `399001.SZ`）

## 官方推荐 vs 本项目策略

迅投知识库（[指数数据](http://dict.thinktrader.net/dictionary/indexes.html)）：

| 场景 | 官方 API | 本项目复盘热路径 |
|------|----------|------------------|
| **当日成交额** | `get_full_tick` → `amount` | ✅ `GET /api/market/full_tick` |
| **历史指数日 K** | `download_history_data` + `get_market_data_ex` | ❌ 禁用（易 BSON 崩溃） |
| **历史缺口** | 需本地已下载数据 | ✅ `reports/market_turnover_daily.json` 每日 tick 累积 |

复盘/校验**默认不调用** `download_batch`、`get_local_data`、`get_market_data_ex`、`get_market_data`。

可选 `--try-history`：先 `download_batch` 指数日线，再 `get_market_data` 子进程补历史并写入缓存（QMT 异常时慎用）。

**推荐补齐近 3 日缺口**（历史缺失时）：

```bash
# 1. 下载指数日线（仅 3 只，勿全市场）
python -c "
from datetime import date, timedelta
import sys; sys.path.insert(0,'skills/_shared')
from common import load_env_files, make_client
import argparse
load_env_files()
c,_=make_client(argparse.Namespace(host='127.0.0.1',port=8080,api_key='test-auto',account_id=None),False)
e=date.today().strftime('%Y%m%d'); s=(date.today()-timedelta(days=12)).strftime('%Y%m%d')
print(c.download_batch(['000001.SH','399106.SZ','399001.SZ'], period='1d', start_time=s, end_time=e))
"

# 2. 读 amount 写入缓存并展示明细
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --host 127.0.0.1 --port 8080 --try-history
```

## 脚本

```bash
# 查看近3日上证+深证成交额明细（亿元）
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --host 127.0.0.1 --port 8080

# 查看近3日成交额明细；历史缺口加 --try-history
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --host 127.0.0.1 --port 8080

# 可选：尝试从本地 K 线补历史（慎用，优先用上一条）
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
  --try-history --host 127.0.0.1 --port 8080

# 兼容旧入口（同上逻辑）
python skills/qmt-bridge-kline-backfill/scripts/backfill_recent_index_kline.py --json
```

## 参数

| 参数 | 说明 |
|------|------|
| `--days` | 需要覆盖的最近交易日数量（默认 3） |
| `--try-history` | 可选尝试 `get_market_data` 补历史（默认关闭） |
| `--json` | 输出机器可读结果 |

## 输出说明

- `ok=true`：近 N 个交易日缓存/tick 均有沪+深成交额
- `ok=false`：列出缺失交易日；连续多日收盘复盘会自动写入缓存
- `method`：默认 `full_tick+cache`

## 排障

1. 当日 tick 失败 → 检查 QMT 登录与行情
2. 历史不足 → 正常（需多日累积）；勿反复跑 `--try-history`
3. BSON / 服务无响应 → **重启 QMT 客户端**，再重启 Bridge

Examiner la source

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Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
SKILL.md contains a duplicated command block in the '脚本' section (two identical lines for the same command).
The skill depends on shared utilities (_shared/market_turnover_util.py, common.py) that are not included in the skill directory itself, which may complicate standalone reuse.
Low GitHub adoption signal
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 24 GitHub stars
Stars/forks activity: 24 stars, 6 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access

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Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: atorber/qmt-trading-skill
Licence: MIT
Version: Unknown
Dernier push GitHub: 22 sept. 2026
Registre mis à jour: 9 oct. 2026
Chemin des instructions: skills/qmt-bridge-kline-backfill/SKILL.md @ 04e8bee0c525

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

60/100

Prometteur

Confiance

52/100

Do not auto-install

Audit

71/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
SKILL.md contains a duplicated command block in the '脚本' section (two identical lines for the same command).
The skill depends on shared utilities (_shared/market_turnover_util.py, common.py) that are not included in the skill directory itself, which may complicate standalone reuse.
Low GitHub adoption signal
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 24 GitHub stars
Stars/forks activity: 24 stars, 6 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access

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      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 71,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "SKILL.md contains a duplicated command block in the '脚本' section (two identical lines for the same command).",
      "The skill depends on shared utilities (_shared/market_turnover_util.py, common.py) that are not included in the skill directory itself, which may complicate standalone reuse.",
      "Low GitHub adoption signal",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 60,
    "label": "Promising"
  },
  "supply": {
    "track": "Finance and quant workflows",
    "scenario": "Finance and quant",
    "maintenance": "21d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "SKILL.md contains a duplicated command block in the '脚本' section (two identical lines for the same command).",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision"
  ],
  "agent_contract": {
    "task_input": "Use qmt-bridge-kline-backfill in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 60/100 Manual review",
      "Audit: 71/100 Needs review",
      "Safety: 35/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "atorber-qmt-bridge-kline-backfill (qmt-bridge-kline-backfill)",
      "install_command": "npx skills add atorber/qmt-trading-skill --skill qmt-bridge-kline-backfill",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "atorber-qmt-bridge-kline-backfill",
      "task": "Use qmt-bridge-kline-backfill in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/atorber-qmt-bridge-kline-backfill",
    "api": "https://www.openagentskill.com/api/agent/skills/atorber-qmt-bridge-kline-backfill",
    "audit": "https://www.openagentskill.com/skills/atorber-qmt-bridge-kline-backfill/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=atorber-qmt-bridge-kline-backfill&task=Use%20qmt-bridge-kline-backfill%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20qmt-bridge-kline-backfill%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20qmt-bridge-kline-backfill%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/atorber-qmt-bridge-kline-backfill/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/atorber-qmt-bridge-kline-backfill"
  }
}

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: atorber
Source: atorber/qmt-trading-skill
Indexé par: Index communautaire OpenAgentSkill

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