geo-infer-time
Time series analysis and temporal modeling for geospatial data. Use when analyzing temporal patterns, forecasting spatial time series, detecting change points, or working with spatio-temporal datasets.
Best use case
geo-infer-time is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Time series analysis and temporal modeling for geospatial data. Use when analyzing temporal patterns, forecasting spatial time series, detecting change points, or working with spatio-temporal datasets.
Teams using geo-infer-time should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/GEO-INFER-TIME/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How geo-infer-time Compares
| Feature / Agent | geo-infer-time | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Time series analysis and temporal modeling for geospatial data. Use when analyzing temporal patterns, forecasting spatial time series, detecting change points, or working with spatio-temporal datasets.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GEO-INFER-TIME ## Instructions ### Core Capabilities - **Time series analysis**: Decomposition, trend detection, seasonality - **Forecasting**: ARIMA, exponential smoothing, temporal GP - **Change detection**: CUSUM, Bayesian change points, structural breaks - **Temporal indexing**: Time-aware spatial queries, temporal resolution management - **Spatio-temporal**: Joint analysis of spatial and temporal dimensions ### Key Imports ```python from geo_infer_time.core.time_series import TimeSeriesAnalyzer from geo_infer_time.core.forecasting import Forecaster from geo_infer_time.core.change_detection import ChangePointDetector ``` ## Examples ```python from geo_infer_time.core.time_series import TimeSeriesAnalyzer analyzer = TimeSeriesAnalyzer(frequency="daily") decomposition = analyzer.decompose(series, method="stl") trend = decomposition.trend seasonal = decomposition.seasonal ``` ## Guidelines ### Integrations - Integrates with SPACE for spatio-temporal analysis - ISO 8601 for all datetime handling - Test: `uv run python -m pytest GEO-INFER-TIME/tests/ -v`