pablodiegoo/machine-learning-lite
src/datapro/data/skills/machine-learning-lite/SKILL.md
Tactical and highly interpretable Machine Learning. Use for: (1) Extracting Feature Importance via Random Forest, (2) Running Permutation Tests, (3) Handling Imbalanced Data (SMOTE).
$ install --global
skillsauthnpx skillsauth add pablodiegoo/data-pro-skill machine-learning-liteInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: May 26, 2026, 6:05 AM41.0s6 files scanned
SKILL.md
- name:
- machine-learning-lite
- description:
- Tactical and highly interpretable Machine Learning. Use for: (1) Extracting Feature Importance via Random Forest, (2) Running Permutation Tests, (3) Handling Imbalanced Data (SMOTE).
Machine Learning Lite
This skill restricts the agent to using simple, highly interpretable Machine Learning methods focused on inference rather than production deployment. Deep learning or black-box predictions are strictly out of scope.
Core Capabilities
1. Interpretability & Testing
permutation_feature_importance.py: Calculates the true model importance of variables by randomly shuffling them.permutation_test_utilities.py: Rigorous statistical testing without assuming underlying data distributions.
Guidelines
- Always prefer Random Forest or Logistic Regression for feature extractability.
- If classes are highly skewed, refer to
references/imbalanced_data_strategies.md.
Related Skills
pablodiegoo/time-series-analysis
testing
VerifiedTrustedCommunity
Comprehensive time-series validation and analysis suite. Handles backtesting of trading and non-trading strategies with support for walk-forward validation (training vs testing windows), performance metric calculation (Sharpe, Drawdown, Win Rate), and event-driven resource allocation simulation. Use for: (1) Validating sequential logic on time-series data, (2) Calculating risk-adjusted performance, (3) Simulating constraints in resource distribution, (4) Detecting look-ahead bias through walk-forward testing.
6SKILL.mdUpdated May 26, 2026
pablodiegoo/survey-analytics
tools
VerifiedTrustedCommunity
Core statistical analysis and pipeline automation for survey datasets. Use for: (1) Running standard Crosstabs, NPS, Top-Box calculations, (2) Generating complete EDA or Analytics notebooks, (3) Quantitative and qualitative processing of questionnaire data.
6SKILL.mdUpdated May 26, 2026
pablodiegoo/strategic-frameworks
development
VerifiedTrustedCommunity
Business-level frameworks and actionable reporting for executives. Use for: (1) Plotting Priority Matrices, (2) Generating Pain Curves, (3) Conversion Funnels, (4) Removing Halo Effects to uncover true sentiment.
6SKILL.mdUpdated May 26, 2026
pablodiegoo/geoprocessing-brazil
testing
VerifiedTrustedCommunity
Normalization and state-mapping of municipal data and generation of professional choropleth maps of Brazil (UF/State level). Use for: (1) Detecting city/state strings and normalizing names, (2) Attaching regional metadata, (3) Generating professional maps integrating survey data with shapefiles.
6SKILL.mdUpdated May 26, 2026