ln-511-code-quality-checker

Solid

Checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Use when implementation tasks are Done and need quality scoring.

AI & Automation 479 stars 67 forks Updated yesterday MIT

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Quality Score: 94/100

Stars 20%
89
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

> **Paths:** File paths (`shared/`, `references/`, `../ln-*`) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If `shared/` is missing, fetch files via WebFetch from `https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}`. # Code Quality Checker **Type:** L3 Worker **Category:** 5XX Quality Analyzes Done implementation tasks with quantitative Code Quality Score based on metrics, MCP Ref validation, and issue penalties. ## Inputs | Input | Required | Source | Description | |-------|----------|--------|-------------| | `storyId` | Yes | args, git branch, kanban, user | Story to process | **Resolution:** Story Resolution Chain. **Status filter:** In Progress, To Review **MANDATORY READ:** Load `shared/references/mcp_tool_preferences.md` and `shared/references/mcp_integration_patterns.md` - use `hex-graph` as the primary path for clone, architecture, and semantic quality evidence when the project is indexed. Fall back to Grep/Read only when graph is unavailable or unsupported. ## Purpose & Scope - Load Story and Done implementation tasks (exclude test tasks) - Calculate Code Quality Score using metrics and issue penalties - **MCP Ref validation:** Verify optimality, best practices, and performance via external sources - Check for DRY/KISS/YAGNI violations, architecture boundary breaks, security issues - Produce quantitative verdict with structured issue list; never e...

Details

Author
levnikolaevich
Repository
levnikolaevich/claude-code-skills
Created
7 months ago
Last Updated
yesterday
Language
JavaScript
License
MIT

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