nixtla-usage-optimizer
Analyze Nixtla usage and optimize cost-effective forecast routing strategies. Use when auditing API usage or reducing costs. Trigger with 'optimize nixtla costs' or 'audit API usage'.
npx skills add majiayu000/claude-skill-registry --skill nixtla-usage-optimizer-intent-solutions-io-plugins-nixtla --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.
# Nixtla Usage Optimizer Audit Nixtla library usage and recommend cost-effective routing strategies. ## Overview This skill analyzes and optimizes Nixtla usage: - **Usage scanning**: Find all TimeGPT and baseline usage - **Cost analysis**: Identify optimization opportunities - **Routing recommendations**: Smart model selection - **ROI assessment**: Cost vs accuracy trade-offs ## Prerequisites **Required**: - Python 3.8+ - Existing Nixtla codebase to audit **No Additional Packages**: Uses only Read, Glob, Grep tools ## Instructions ### Step 1: Scan Repository Find all Nixtla library usage: ```bash grep -r "NixtlaClient" --include="*.py" . grep -r "StatsForecast" --include="*.py" . grep -r "MLForecast" --include="*.py" . ``` ### Step 2: Analyze Patterns Categorize usage by: - Location (experiments, pipelines, notebooks) - Frequency (how often called) - Data characteristics (simple vs complex patterns) ### Step 3: Generate Report Create `000-docs/nixtla_usage_report.md` with: - Executive summary - Usage analysis - Recommendations - ROI assessment ### Step 4: Implement Routing Apply recommendations: - Replace TimeGPT with baselines for simple patterns - Add TimeGPT for high-value forec
- Overview
- Prerequisites
- Instructions
- Step 1: Scan Repository
- Step 2: Analyze Patterns
- Step 3: Generate Report
- Step 4: Implement Routing
- Output
- Error Handling
- Examples
- Example 1: Audit Existing Project
- Example 2: No TimeGPT Yet
- Resources
grep -r "NixtlaClient" --include="*.py" . grep -r "StatsForecast" --include="*.py" . grep -r "MLForecast" --include="*.py" .
What does the nixtla-usage-optimizer skill do?
Analyze Nixtla usage and optimize cost-effective forecast routing strategies. Use when auditing API usage or reducing costs. Trigger with 'optimize nixtla costs' or 'audit API usage'.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill nixtla-usage-optimizer-intent-solutions-io-plugins-nixtla --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 majiayu000/claude-skill-registry, a repository with 534 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.