Data Pipeline Processor Metrics

Validates, tests, and scores the quality of skills within a claude-skills ecosystem using Python scripts that check structure, syntax, runtime, and multi-dimensional quality metrics.

Scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues before deployment. Intercepts deploy commands and blocks until critical items pass.

Provides technical leadership frameworks for architecture decisions, engineering team scaling, technology strategy, and technical debt assessment.

Design, review, and operate SLOs, SLIs, and error budgets with multi-window burn-rate alerts and automated validation.

Generates CI/CD pipelines, Terraform modules, and Kubernetes deployment manifests with health-check gates and rollback support for AWS, GCP, and Azure.

Converts a markdown code review or PR writeup with diff blocks and severity-tagged callouts into a single-file two-column HTML review with jump navigation and a named reviewer footer.