// Generate and configure Nixtla Skills using the CLI for forecasting workflows. Use when installing or updating skills. Trigger with 'install nixtla skills' or 'update nixtla'.
Generate benchmarking pipelines to compare forecasting models and summarize accuracy/speed trade-offs. Use when evaluating TimeGPT vs StatsForecast/MLForecast/NeuralForecast on a dataset. Trigger with "benchmark models", "compare TimeGPT vs StatsForecast", or "model selection".
Research and summarize Nixtla ecosystem updates and time-series forecasting content from the web and GitHub. Use when gathering release notes, recent changes, or best-practice references. Trigger with "Nixtla updates", "what's new with TimeGPT", or "find time-series papers".
Generate production-ready TimeGPT forecasting pipeline code from requirements. Use when scaffolding a pipeline with validation, logging, visualization, and repeatable runs. Trigger with "create TimeGPT pipeline", "build TimeGPT integration", or "generate forecast code".
Analyze Nixtla baseline forecasting results (sMAPE/MASE on M4 or other benchmark datasets). Use when the user asks about baseline performance, model comparisons, or metric interpretation for Nixtla time-series experiments. Trigger with "baseline review", "interpret sMAPE/MASE", or "compare AutoETS vs AutoTheta".
Orchestrate 6-phase changelog generation workflow with AI synthesis, multi-source data fetching (GitHub/Slack/Git), quality validation, and automated PR creation. Use when automating release notes, weekly changelogs, or documentation updates. Trigger with "generate changelog", "weekly changelog", or "automate release notes".
Analyze and explain TimeGPT forecast results in plain English. Generates executive summaries with driver analysis. Use when stakeholders need forecast explanations, board presentations, or compliance documentation. Trigger with "explain forecast", "why is the forecast", "forecast narrative".
| name | nixtla-skills-bootstrap |
| description | Generate and configure Nixtla Skills using the CLI for forecasting workflows. Use when installing or updating skills. Trigger with 'install nixtla skills' or 'update nixtla'. |
| allowed-tools | Read,Glob,Grep |
| version | 1.0.0 |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| license | MIT |
Install or update Nixtla Skills in the current project using the nixtla-skills CLI.
This skill manages Nixtla Skills installation:
.claude/skills/Skills persist locally until explicitly updated or removed.
Required:
nixtla-skills CLI toolInstallation:
pip install nixtla-claude-skills-installer
Verify CLI:
which nixtla-skills || echo "NOT_FOUND"
Select installation mode:
init - First-time installationupdate - Refresh existing skillsVerify nixtla-skills CLI is installed:
nixtla-skills --version
If not found, install with: pip install nixtla-claude-skills-installer
For init:
nixtla-skills init
For update:
nixtla-skills update
ls -1d .claude/skills/nixtla-* 2>/dev/null | sort
After installation:
.claude/skills/nixtla-timegpt-lab/ - Core forecasting skill.claude/skills/nixtla-experiment-architect/ - Experiment scaffolding.claude/skills/nixtla-schema-mapper/ - Data transformation.claude/skills/nixtla-skills-bootstrap/ - This skillError: nixtla-skills: command not found
Solution: pip install nixtla-claude-skills-installer
Error: Permission denied
Solution: Check write permissions on .claude/skills/
Error: Skills directory already exists
Solution: Use update instead of init
Error: No skills installed after completion
Solution: Verify CLI version: nixtla-skills --version
nixtla-skills init
Output:
Installing Nixtla Skills...
Created .claude/skills/nixtla-timegpt-lab/
Created .claude/skills/nixtla-experiment-architect/
Created .claude/skills/nixtla-schema-mapper/
Created .claude/skills/nixtla-skills-bootstrap/
Installation complete!
nixtla-skills update
Output:
Updating Nixtla Skills...
Updated 4 skills to latest version.
Installed location: .claude/skills/nixtla-skills-bootstrap/