time-series-analyzer
Skill for time series analysis and forecasting
Profile →npx skills add a5c-ai/babysitter --skill time-series-analyzer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Time Series Analyzer Skill ## Purpose Analyze time series data for trends, seasonality, and patterns, and generate forecasts using appropriate methods. ## Capabilities - Decompose time series - Identify patterns - Fit ARIMA models - Generate forecasts - Assess stationarity - Evaluate accuracy ## Usage Guidelines 1. Prepare time series 2. Assess stationarity 3. Identify patterns 4. Select model 5. Generate forecasts 6. Evaluate accuracy ## Process Integration Works within scientific discovery workflows for: - Trend analysis - Forecasting - Pattern detection - Temporal modeling ## Configuration - Model selection - Forecast horizons - Decomposition methods - Accuracy metrics ## Output Artifacts - Decomposition plots - Model diagnostics - Forecast results - Accuracy reports
- Purpose
- Capabilities
- Usage Guidelines
- Process Integration
- Configuration
- Output Artifacts
What does the time-series-analyzer skill do?
Skill for time series analysis and forecasting
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill time-series-analyzer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.