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Use when tasks need local market Parquet data, factor artifacts, backtest data, or model files through DataManager.

Skill by quantskills

IndexedGPL-3.0★ 64
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/quantskills-store

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About

Use when tasks need local market Parquet data, factor artifacts, backtest data, or model files through DataManager.

Use cases: data

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What's inside

Skill name
store
Description
Use when tasks need local market Parquet data, factor artifacts, backtest data, or model files through DataManager.
License
GPL-3.0
Instructions
97 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (5)

  • SKILL.md
  • __init__.py
  • adjusted_quality.py
  • data_manager.py
  • workspace.py

SKILL.md (first lines)

# Store

`skills/store` owns reusable file storage for market data and generic research
artifacts. The public project uses explicit strategy universes and does not
maintain a central universe registry.

## DataManager

```python
from skills.store.data_manager import DataManager, DataQualityReport, validate_ohlcv
from skills.store.workspace import resolve_workspace_paths
```

The data root comes from `QUANTSPACE_DATA_ROOT`, otherwise the repository
`data/` directory.

`resolve_workspace_paths()` centralizes `QUANTSPACE_WORKSPACE_ROOT`,
`QUANTSPACE_DATA_ROOT`, and `QUANTSPACE_REPORTS_ROOT` without creating any
directories. Runtime entrypoints use it instead of modifying `sys.path` or
independently guessing the repository root.

Supported layout:

```text
data/market/<frequency>/<symbol>.parquet
data/adj_factor/<symbol>.parquet
data/factors/<namespace>/
data/correlation/
data/backtest/
data/models/
data/export/
```

The subdirectory below `data/market/` is a storage directory/data-set key. Its
base part is the real bar frequency, while an optional `_adj` suffix records
the price-adjustment state:

| Directory key | Real `freq` | Meaning |
|---------------|-------------|---------|
| `1d` | `1d` | Daily unadjusted (raw) bars |
| `1d_adj` | `1d` | Adjusted daily bars |
| `5m` | `5m` | 5-minute unadjusted bars |
| `5m_adj` | `5m` | Adjusted 5-minute bars |

Therefore `data/market/1d_adj/` does **not** represent a frequency named
`1d_adj`; its `freq` is still `1d`, and `1d_adj` is only the directory name
indicating adjusted `1d` data. The same convention applies to other bar
intervals: `<freq>_adj` stores adjusted bars whose actual frequency is
`<freq>`.

`DataManager` names its directory-selector parameter `frequency`. Pass the full directory key to `read_symbol` / `read_symbols` /
`save_symbol` (for example, `frequency="1d_adj"`) so it resolves the intended
path. Do not reuse that suffixed value as the semantic `freq` or pass it to an
upstream market-data API; use `freq="1d"` there.

Main methods:

- `read_symbol`, `read_symbols`, `save_symbol`
- `import_symbol_csv`, `import_combined_csv`, `list_symbols`
- `save_factor`, `read_factor`, `factor_namespace_dir`, `factor_filename`
- `save_factor_correlation`, `read_factor_correlation`
- `save_backtest_run`, `read_backtest_summary`, `read_backtest_run`
- `list_models`, `read_model_metadata`

`read_symbols` returns a MultiIndex `(symbol, eob)` panel and reports every
missing symbol in one `FileNotFoundError`.

`DataManagerArtifactStore` (`skills.factor_mining.adapters.store`) persists
factor-mining research artifacts under
`data/factors/<namespace>/artifacts/<kind>/<artifact_id>.json` (path segments are
validated; resolved paths must stay under that namespace). It reuses
`save_factor` / `factor_filename` for explicit wide-pivot caches keyed by a
content-addressed `cache_key`. `DataManager.namespaced_artifact_dir(namespace,
*parts)` is the generic helper that returns (and creates)
`data/factors/<namespace>/<parts...>/`; there is no second catalog.

```python
from skills.store.data_manager import DataManager

panel = DataManager().read_symbols(
    ["SHSE.510300", "SHSE.510500"],
    frequency="1d_adj",
)
```

## Boundary Rules

- Keep market and generic research files here.
- Pass strategy universes as explicit symbol lists owned by the caller.
- Treat factor/backtest/model subdirectory names as artifact namespaces, not
  centrally managed instrument universes.
- Do not add strategy identity schemas or a second experiment catalog.

## CLI command reference

<!-- BEGIN GENERATED: qs commands -->

Transport: `--input-json FILE|-`, `--preview N`, and `--log-level LEVEL`; flags override JSON. Use `--print-template [FIELD]` for fillable templates.

### Shared parameter groups

#### `OutputOptions`

| Option | Type / default | Description |
|---|---|---|
| `--output` | `path?` / `null` | Explicit output path outside managed store namespaces. |
| `--overwrite` | `boolean` / `false` | Allow replacing an existing output artifact. |
| `--data-root` | `path?` / `null` | Managed data root; otherwise QUANTSPACE_DATA_ROOT or repository data/. |

### `uv run qs store info`

Inspect the local data store inventory.

Priority: P0. Side effects: read-only.

| Option | Type / default | Description |
|---|---|---|
| `--data-root` | `path?` / `null` | Managed data root; otherwise QUANTSPACE_DATA_ROOT or repository data/. |

From quantskills/agent-quantspace, GPL-3.0.

More from quantskills/agent-quantspace

Signals

Stars
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Forks
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Open issues
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Last commit (this folder)
Aug 5, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
GPL-3.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

store skill. Agent Mart. https://agentmart.dev/skills/quantskills-store (last updated 2026-10-24)