code-review-pipeline
The code-review-pipeline skill performs systematic code review across four dimensions: correctness (logic errors, edge cases, type safety), security (injection vectors, authentication, data exposure), performance (algorithmic complexity, memory leaks, optimization), and maintainability (naming, documentation, test coverage). Use this skill for post-implementation reviews, pre-merge pull request validation, security audits, and technical debt assessment, with confidence-gated reporting that surfaces only high-confidence issues and includes automated remediation loops.
git clone --depth 1 https://github.com/a5c-ai/babysitter /tmp/code-review-pipeline && cp -r /tmp/code-review-pipeline/library/methodologies/everything-claude-code/skills/code-review-pipeline ~/.claude/skills/code-review-pipelineSKILL.md
# Code Review Pipeline ## Overview Multi-dimensional code review methodology adapted from the Everything Claude Code project. Reviews across 4 dimensions with confidence-gated issue reporting and automated remediation loops. ## Review Dimensions ### Dimension 1: Correctness - Logic errors and off-by-one mistakes - Edge case handling (null, undefined, empty, boundary) - Type safety (no implicit any, proper narrowing) - Error handling completeness - Floating promise detection - Race condition analysis ### Dimension 2: Security - Injection vectors (SQL, XSS, command, template) - Authentication and authorization gaps - Data exposure (PII, credentials, internal state) - Dependency vulnerabilities (known CVEs) - Input validation completeness ### Dimension 3: Performance - Algorithmic complexity (O(n^2) detection) - Memory leaks (event listeners, closures, caches) - Unnecessary allocations in hot paths - Database query optimization (N+1, missing indexes) - Bundle size impact ### Dimension 4: Maintainability - Naming clarity and consistency - Documentation completeness (JSDoc, inline comments) - Test coverage adequacy - Coupling analysis (afferent/efferent) - File organization compliance ## Confidence Gating - Score each issue 0-100 on confidence - Only report issues >= 80% confidence - Prevents false positive noise - Higher confidence for clear patterns, lower for heuristic matches ## Remediation Loop - Prioritize: critical > high > medium > low - Apply fixes via refactor-cleaner agent - Re-review after remediation - Maximum 2 remediation cycles - Exit when no critical/high issues remain ## When to Use - Post-implementation review - Pre-merge PR review - Security audit - Technical debt assessment ## Agents Used - `code-reviewer` (primary) - `refactor-cleaner` (remediation)
Review TypeScript code changes for consistency, type safety, and monorepo patterns across babysitter packages
Generate and validate documentation for @a5c-ai/babysitter-sdk CLI commands and exported APIs
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
Architect code review with DRY, YAGNI, abstraction, and test coverage principle enforcement