code-review-pipeline

Solid

Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.

Code & Development 814 stars 53 forks Updated today MIT

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Quality Score: 93/100

Stars 20%
97
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
90
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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-c...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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