foryourhealth111-pixel/regression-analysis-helper
bundled/skills/regression-analysis-helper/SKILL.md
Build and diagnose regression analyses for continuous targets or effect estimation. Use for coefficient interpretation, residual checks, and model comparison; not for causal identification or clustering.
$ install --global
skillsauthnpx skillsauth add foryourhealth111-pixel/vco-skills-codex regression-analysis-helperInstall 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: Apr 26, 2026, 3:50 AM283.3s1 file scanned
SKILL.md
- name:
- regression-analysis-helper
- description:
- |
- allowed-tools:
- Read, Write, Edit, Bash, Grep
- version:
- 1.0.0
- license:
- MIT
- author:
- Jeremy Longshore <[email protected]>
Regression Analysis Helper
Purpose
Use this skill when the next question is "what does the regression say?" rather than "which broad workflow should own the whole ML task?"
In governed routing, regression ownership normally belongs to performing-regression-analysis.
When to Use
Use this skill when:
- Fitting linear or generalized regression models
- Interpreting coefficients, residuals, and diagnostics
- Comparing alternative regression specifications for a continuous outcome
Not For / Boundaries
- Main routed ownership of a regression task: use
performing-regression-analysis - Causal identification and counterfactual claims: use
performing-causal-analysis - Unsupervised grouping: use
running-clustering-algorithms - General report packaging: use
scientific-reporting
Typical Outputs
- Regression specification recommendations
- Diagnostic summaries for assumptions and fit
- Notes on effect size interpretation and multicollinearity risk
Related Skills
correlation-analyzerfor pre-model screeningperforming-regression-analysisas the routed owner when regression is the main taskscientific-reportingwhen the regression needs to become a deliverable report
Related Skills
foryourhealth111-pixel/shap
development
VerifiedTrustedCommunity
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
1,760SKILL.mdUpdated Apr 27, 2026
foryourhealth111-pixel/sentry
development
VerifiedTrustedCommunity
Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.
1,760SKILL.mdUpdated Apr 27, 2026
foryourhealth111-pixel/senior-prompt-engineer
development
VerifiedTrustedCommunity
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
1,760SKILL.mdUpdated Apr 27, 2026
foryourhealth111-pixel/senior-ml-engineer
development
VerifiedTrustedCommunity
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
1,760SKILL.mdUpdated Apr 27, 2026