intent-solutions-io/nixtla-usage-optimizer
003-skills/.claude/skills-backup-20251210-155310/nixtla-usage-optimizer/SKILL.md
Audits Nixtla library usage and recommends cost-effective routing strategies. Scans TimeGPT, StatsForecast, and MLForecast patterns, identifies cost optimization opportunities, generates comprehensive usage reports, and suggests smart routing between models. Activates when user needs cost optimization, API usage audit, routing strategy design, or Nixtla cost reduction.
$ install --global
skillsauthnpx skillsauth add intent-solutions-io/plugins-nixtla nixtla-usage-optimizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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3
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9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
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mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
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Socket.devSupply chain security analysis
50%
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VirusTotalMulti-engine malware detection
50%
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CrowdStrikeAdvanced threat intelligence
50%
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OSV-ScannerOpen Source Vulnerability database check
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OWASP Dep-Check
50%
Last scanned: Apr 5, 2026, 11:13 PM8.4s5 files scanned
SKILL.md
- name:
- nixtla-usage-optimizer
- description:
- Audits Nixtla library usage and recommends cost-effective routing strategies. Scans TimeGPT, StatsForecast, and MLForecast patterns, identifies cost optimization opportunities, generates comprehensive usage reports, and suggests smart routing between models. Activates when user needs cost optimization, API usage audit, routing strategy design, or Nixtla cost reduction.
- allowed-tools:
- Read,Glob,Grep
- version:
- 1.0.0
- license:
- MIT
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:
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 forecasts
- Implement fallback chains
Output
- 000-docs/nixtla_usage_report.md: Comprehensive usage report
- routing_rules.json: Machine-readable routing logic (optional)
Error Handling
-
Error:
No Nixtla usage foundSolution: Repository may not use Nixtla - recommend adoption -
Error:
Cannot determine cost impactSolution: Add usage metrics or API call logging -
Error:
Mixed usage patternsSolution: Report both opportunities, prioritize high-impact -
Error:
No baseline models foundSolution: Recommend adding StatsForecast for fallback
Examples
Example 1: Audit Existing Project
Scan results:
Found Nixtla usage:
- TimeGPT: 12 locations
- StatsForecast: 5 locations
- MLForecast: 2 locations
Recommendations:
1. Replace TimeGPT in 4 low-impact areas (save ~40%)
2. Add fallback to StatsForecast baselines
3. Keep TimeGPT for high-value forecasts
Example 2: No TimeGPT Yet
Scan results:
Found Nixtla usage:
- StatsForecast: 8 locations
- TimeGPT: 0 locations
Recommendations:
1. Add TimeGPT for 2 high-value forecasts
2. Keep baselines for simple patterns
3. Implement tiered routing
Resources
- Routing Framework: See Error Handling section
- TimeGPT Pricing: https://nixtla.io/pricing
- StatsForecast Docs: https://nixtla.github.io/statsforecast/
Related Skills:
nixtla-experiment-architect: Validate routing decisionsnixtla-timegpt-finetune-lab: Evaluate fine-tuning ROInixtla-prod-pipeline-generator: Implement routing in production
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