levnikolaevich/claude-code-skills
Overview
This skill audits code principles (DRY, KISS, YAGNI), error handling, and DI/init patterns to produce structured findings and a compliance score. It runs targeted pattern-based scans, maps each finding to refactoring recommendations, and outputs a single report file with an extended JSON block for cross-domain DRY analysis. The worker is domain-aware and returns severity, location, effort, pattern_id, and pattern_signature for each finding.
How this skill works
The auditor parses the coordinator-provided contextStore to determine scan_path, tech_stack, principles, and output_dir, then loads language-specific detection patterns. It runs Grep/Glob detections constrained by exclusions, matches findings to refactoring patterns via the decision tree, and tags each result with severity, effort, location, and pattern_signature. Finally it computes a penalty-based score, writes the full markdown report (including a <!-- FINDINGS-EXTENDED --> JSON block for DRY findings) in a single write, and returns a concise summary to the coordinator.
When to use it
- During automated codebase quality gates before major releases
- As part of continuous architecture reviews or technical debt sprints
- When onboarding a new domain or verifying cross-domain duplication
- Before refactoring initiatives to prioritize high-impact duplication
- To validate error handling and DI patterns across services
Best practices
- Run domain-aware scans to limit noise and surface domain-specific issues
- Ensure detection_patterns and refactoring_decision_tree references are up-to-date for accurate matching
- Exclude generated, vendor, and migrations directories to avoid false positives
- Treat pattern_signature as the canonical key for cross-domain DRY correlation
- Use effort estimates (S/M/L) to prioritize fixes alongside severity
Example use cases
- Detect identical authentication logic duplicated across microservices and recommend extraction into a shared module
- Find async route handlers missing try/catch and flag critical user-facing endpoints as high severity
- Identify unnecessary factories or single-implementation abstractions and recommend simplification
- Surface repeated validation logic (email/password) with a pattern_signature for cross-repo consolidation
- Verify presence of a centralized ErrorHandler and bootstrap/DI initialization patterns
FAQ
No. The skill only reports findings and recommendations; it never performs automatic fixes.
How are cross-domain duplications identified?
DRY findings include a pattern_signature; the coordinator uses these normalized signatures across domains to detect cross-domain duplication.
6 skills
This skill audits code principles (DRY, KISS, YAGNI, error handling, DI) and returns actionable findings with location, severity, and recommendations.
This skill identifies dead code, unused imports, and backward compatibility shims to improve maintainability and code health across projects.
This skill audits code quality by detecting complexity, nesting, long methods, and bad signatures, returning actionable findings and improvement
This skill audits build health by checking compiler, linter, tests, and config, returning structured findings with severity and actionable recommendations.
This skill audits application lifecycle in a worker, analyzes startup order, shutdown, probes, and returns an actionable compliance score.
This skill audits observability in codebases, identifying logging, health checks, metrics, and tracing gaps to improve reliability with actionable findings.
