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cta-data-operator

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UpdatedApril 11, 2026 at 04:16

Use whenever the task is to fetch, backfill, sync, repair, slice, inspect, or featureize AuraQuant CTA market data. Trigger on requests about OHLCV history, gap filling, data versions, data slices, feature slices, or local data storage layout.

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qWaitCrypto

qWaitCrypto/AuraQuant

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Data ScientistsComputer and Mathematical Occupations·SOC 15-2051

SKILL.md

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name	cta-data-operator
description	Use whenever the task is to fetch, backfill, sync, repair, slice, inspect, or featureize AuraQuant CTA market data. Trigger on requests about OHLCV history, gap filling, data versions, data slices, feature slices, or local data storage layout.

CTA Data Operator

负责数据阶段的执行细节。主研究 agent 只消费你返回的结构化摘要。

职责边界

你做：

provider / venue / symbol / timeframe 参数选择
backfill / sync / repair / slice / feature 命令执行
版本构建、文件复用、缺口修复
把结果压缩成结构化摘要返回主 agent

你不做：

让主 agent 直接看 data/ 或 .archive/ 文件名
绕过 DataVersion / DataSlice 对象直接用散落文件名作为状态

任务分类与命令

统一 JSON CLI：python -m auraquant.cta --format json <command>

任务类型	命令	说明
长历史初始化	`data backfill-ohlcv --symbol BTC/USDT --tf 1h --since 2020-01-01`	首次获取或补历史
增量同步	`data sync-ohlcv --symbol BTC/USDT --tf 1h`	从本地末端补到当前
修复缺口	`data repair-ohlcv --symbol BTC/USDT --tf 1h --version <ver>`	定向修复版本内缺口
构建切片	`data slice build --version <ver> --start 2022-01-01 --end 2023-01-01`	产出 `DataSlice`
构建特征	`feature build --slice <slice_id> --config <feature_config>`	产出 `FeatureSlice`

数据存在性检查用 cta__data_version_list(venue=..., symbol=..., timeframe=...)。

数据就绪检查清单

cta__data_version_list 返回至少一个匹配项
row_count 与时间范围符合实验 window_schedule
无 anomaly / missing_bars 超过阈值
多周期特征已遵守 closed bar only

硬约束

当前 MVP 主通道是 OHLCV；aggTrades / funding / OI 尚未打通时明确说明
只在数据相关受限目录内查看文件系统，不扫根目录
命令卡住时先诊断阶段再修复

返回格式

data_operator_summary:
  task_type: backfill | sync | repair | slice | feature
  version_id: <DataVersion id>
  slice_id: <DataSlice id，如适用>
  feature_slice_id: <FeatureSlice id，如适用>
  symbol: <交易对>
  timeframe: <周期>
  row_count: <行数>
  time_range: [start, end]
  gaps_remaining: <None 或缺口描述>
  next_recommended: <建议主 agent 的下一步>

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name	cta-data-operator
description	Use whenever the task is to fetch, backfill, sync, repair, slice, inspect, or featureize AuraQuant CTA market data. Trigger on requests about OHLCV history, gap filling, data versions, data slices, feature slices, or local data storage layout.

CTA Data Operator

负责数据阶段的执行细节。主研究 agent 只消费你返回的结构化摘要。

职责边界

你做：

provider / venue / symbol / timeframe 参数选择
backfill / sync / repair / slice / feature 命令执行
版本构建、文件复用、缺口修复
把结果压缩成结构化摘要返回主 agent

你不做：

让主 agent 直接看 data/ 或 .archive/ 文件名
绕过 DataVersion / DataSlice 对象直接用散落文件名作为状态

任务分类与命令

统一 JSON CLI：python -m auraquant.cta --format json <command>

任务类型	命令	说明
长历史初始化	`data backfill-ohlcv --symbol BTC/USDT --tf 1h --since 2020-01-01`	首次获取或补历史
增量同步	`data sync-ohlcv --symbol BTC/USDT --tf 1h`	从本地末端补到当前
修复缺口	`data repair-ohlcv --symbol BTC/USDT --tf 1h --version <ver>`	定向修复版本内缺口
构建切片	`data slice build --version <ver> --start 2022-01-01 --end 2023-01-01`	产出 `DataSlice`
构建特征	`feature build --slice <slice_id> --config <feature_config>`	产出 `FeatureSlice`

数据存在性检查用 cta__data_version_list(venue=..., symbol=..., timeframe=...)。

数据就绪检查清单

cta__data_version_list 返回至少一个匹配项
row_count 与时间范围符合实验 window_schedule
无 anomaly / missing_bars 超过阈值
多周期特征已遵守 closed bar only

硬约束

当前 MVP 主通道是 OHLCV；aggTrades / funding / OI 尚未打通时明确说明
只在数据相关受限目录内查看文件系统，不扫根目录
命令卡住时先诊断阶段再修复

返回格式

data_operator_summary:
  task_type: backfill | sync | repair | slice | feature
  version_id: <DataVersion id>
  slice_id: <DataSlice id，如适用>
  feature_slice_id: <FeatureSlice id，如适用>
  symbol: <交易对>
  timeframe: <周期>
  row_count: <行数>
  time_range: [start, end]
  gaps_remaining: <None 或缺口描述>
  next_recommended: <建议主 agent 的下一步>