What metrics can be tracked with Baseline Governance?

By default, it tracks test pass rates, TypeScript error counts, ESLint warnings, and bundle sizes, but the framework can be extended to any metric stored in a JSON format.

What is a 'ratchet' mechanism in software quality?

A ratchet mechanism is a policy where quality metrics can only improve. Once a higher level of quality (e.g., fewer lint errors) is achieved, the baseline is updated, and the system prevents any future regressions from being merged.

Does this skill integrate with my CI/CD pipeline?

Yes, it includes implementation patterns for CI scripts (like baseline-check.sh) that automatically enforce these policies during the build process.

How does this skill handle intentional regressions?

It provides a structured workflow where developers must document the reason, provide a follow-up plan, and obtain specific approval levels (like Tech Lead approval) for acceptable regressions like major dependency upgrades.

Baseline Governance

Name: Baseline Governance
Author: nikhillinit

bynikhillinit

Security & Testing

Enforces quality standards and prevents software regressions by implementing a "ratchet" mechanism for core project metrics.

About

The Baseline Governance skill establishes a policy-driven approach to maintaining and improving software quality through automated baseline tracking. It monitors essential metrics—such as test pass rates, TypeScript errors, ESLint warnings, and bundle sizes—ensuring that quality only moves upward or remains stable. By treating these baselines as a floor, the skill prevents the gradual accumulation of technical debt and ensures that any necessary regressions are intentionally documented, justified, and approved rather than accidentally merged.

Key Features

0 GitHub stars
Bundle size monitoring to prevent performance degradation exceeding defined thresholds.
Incremental quality enforcement using a "ratchet" mechanism that prevents metric backsliding.
Automated tracking and comparison of TypeScript, ESLint, and test pass rate baselines.
Structured approval workflows for intentional regressions during major refactors or upgrades.
CI/CD integration guidance for blocking non-compliant pull requests automatically.

Use Cases

Stabilizing large codebases by ensuring the test pass rate never decreases during refactoring.
Managing long-term migrations to stricter TypeScript or Linting rules without blocking daily feature work.
Preventing accidental performance regressions in production bundles by locking maximum sizes.

About

Key Features

0 GitHub stars
Bundle size monitoring to prevent performance degradation exceeding defined thresholds.
Incremental quality enforcement using a "ratchet" mechanism that prevents metric backsliding.
Automated tracking and comparison of TypeScript, ESLint, and test pass rate baselines.
Structured approval workflows for intentional regressions during major refactors or upgrades.
CI/CD integration guidance for blocking non-compliant pull requests automatically.

Use Cases

Stabilizing large codebases by ensuring the test pass rate never decreases during refactoring.
Managing long-term migrations to stricter TypeScript or Linting rules without blocking daily feature work.
Preventing accidental performance regressions in production bundles by locking maximum sizes.