timedatamodel-skill
Guides creation and manipulation of TimeDataModel objects (TimeSeries, TimeSeriesTable) with rich metadata for energy, forecasting, and time
Open source Repository Open in the app JSON README (API)
About
Guides creation and manipulation of TimeDataModel objects (TimeSeries, TimeSeriesTable) with rich metadata for energy, forecasting, and time series data pipelines.
Details
- Kind
- Plugins
- Topic
- No topic detected
- Publisher
- rebase-energy
- Origin
- marketplace
- Category
- ferramentas
- Last push
- 2026-03-23T13:23:06Z
- Repository state
- ativo
- Language
- HTML
- License
- MIT
- Added
- 2026-08-30 01:48:58
- Updated
- 2026-08-30 01:48:58
- Origin id
rebase-energy/timedatamodel-skill/timedatamodel-skill
README
# TimeDataModel — Claude Code Plugin A Claude Code skill that makes Claude an expert in the [TimeDataModel](https://github.com/rebase-energy/TimeDataModel) Python library — the standard for self-describing, bi-temporal time series data in energy and forecasting pipelines. Once installed, Claude automatically applies this knowledge whenever you work with `TimeSeries` or `TimeSeriesTable` objects. No commands to remember — it just works. ## What Claude learns - **DataShape selection** — when to use `SIMPLE`, `VERSIONED`, `CORRECTED`, or `AUDIT` based on your modeling needs - **Creating time series** — from pandas, Polars, NumPy, and PyArrow, with the right `Frequency`, `DataType`, and metadata - **Bi-temporal modeling** — structuring forecasts with `knowledge_time` + `valid_time` for full auditability - **Enums** — complete `Frequency`, `DataType` hierarchy, and `TimeSeriesType` reference - **Workflows** — import/export, slicing, unit conversion (pint), geospatial filtering, and validation ## Installation Search for it in Claude Code: ``` /find-skills timedatamodel ``` Or install directly: ``` /plugin install timedatamodel ``` ## Example After installing, just describe what you want: > *"Create a versioned TimeSeries of hourly wind power forecasts from this pandas DataFrame"* Claude will produce correct, idiomatic TimeDataModel code — right DataShape, right enums, UTC-aware timestamps — without you needing to look anything up. ## About TimeDataModel [TimeDataModel](https://github.com/rebase-energy/TimeDataModel) is an open-source Python library by [Rebase Energy](https://rebase.energy) for modeling time series data with rich, machine-readable metadata. It is designed for energy systems, forecasting, and any domain where data provenance and bi-temporality matter. ``` pip install timedatamodel ```