ln-501-code-quality-checker

name	ln-501-code-quality-checker
description	Worker that checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates architectural decisions via MCP Ref: (1) Optimality - is chosen approach the best? (2) Compliance - does it follow best practices? (3) Performance - algorithms, configs, bottlenecks. Reports issues with SEC-, PERF-, MNT-, ARCH-, BP-, OPT- prefixes.

Code Quality Checker

Analyzes Done implementation tasks with quantitative Code Quality Score based on metrics, MCP Ref validation, and issue penalties.

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 edits Linear or kanban

Code Metrics

Metric	Threshold	Penalty
Cyclomatic Complexity	≤10 OK, 11-20 warning, >20 fail	-5 (warning), -10 (fail) per function
Function size	≤50 lines OK, >50 warning	-3 per function
File size	≤500 lines OK, >500 warning	-5 per file
Nesting depth	≤3 OK, >3 warning	-3 per instance
Parameter count	≤4 OK, >4 warning	-2 per function

Code Quality Score

Formula: Code Quality Score = 100 - metric_penalties - issue_penalties

Issue penalties by severity:

Severity	Penalty	Examples
high	-20	Security vulnerability, O(n²)+ algorithm, N+1 query
medium	-10	DRY violation, suboptimal approach, missing config
low	-3	Naming convention, minor code smell

Score interpretation:

Score	Status	Verdict
90-100	Excellent	PASS
70-89	Acceptable	CONCERNS
<70	Below threshold	ISSUES_FOUND

Issue Prefixes

Prefix	Category	Default Severity	MCP Ref
SEC-	Security (auth, validation, secrets)	high	—
PERF-	Performance (algorithms, configs, bottlenecks)	medium/high	✓ Required
MNT-	Maintainability (DRY, SOLID, complexity)	medium	—
ARCH-	Architecture (layers, boundaries, patterns)	medium	—
BP-	Best Practices (implementation differs from recommended)	medium	✓ Required
OPT-	Optimality (better approach exists for this goal)	medium	✓ Required

PERF- subcategories:

Prefix	Category	Severity
PERF-ALG-	Algorithm complexity (Big O)	high if O(n²)+
PERF-CFG-	Package/library configuration	medium
PERF-PTN-	Architectural pattern performance	high
PERF-DB-	Database queries, indexes	high

When to Use

• Invoked by ln-500-story-quality-gate Pass 1 (first gate)
• All implementation tasks in Story status = Done
• Before regression testing (ln-502) and test planning (ln-510)

Workflow (concise)

1. Load Story (full) and Done implementation tasks (full descriptions) via Linear; skip tasks with label "tests".
2. Collect affected files from tasks (Affected Components/Existing Code Impact) and recent commits/diffs if noted.
3. Calculate code metrics:
   • Cyclomatic Complexity per function (target ≤10)
   • Function size (target ≤50 lines)
   • File size (target ≤500 lines)
   • Nesting depth (target ≤3)
   • Parameter count (target ≤4)

3.5) MCP Ref Validation (MANDATORY for code changes):

Level 1 — OPTIMALITY (OPT-):

• Extract goal from task (e.g., "user authentication", "caching", "API rate limiting")
• Research alternatives: ref_search_documentation("{goal} approaches comparison {tech_stack} 2026")
• Compare chosen approach vs alternatives for project context
• Flag suboptimal choices as OPT- issues

Level 2 — BEST PRACTICES (BP-):

• Research: ref_search_documentation("{chosen_approach} best practices {tech_stack} 2026")
• For libraries: query-docs(library_id, "best practices implementation patterns")
• Flag deviations from recommended patterns as BP- issues

Level 3 — PERFORMANCE (PERF-):

• PERF-ALG: Analyze algorithm complexity (detect O(n²)+, research optimal via MCP Ref)
• PERF-CFG: Check library configs (connection pooling, batch sizes, timeouts) via query-docs
• PERF-PTN: Research pattern pitfalls: ref_search_documentation("{pattern} performance bottlenecks")
• PERF-DB: Check for N+1, missing indexes via query-docs(orm_library_id, "query optimization")

Triggers for MCP Ref validation:

• New dependency added (package.json/requirements.txt changed)
• New pattern/library used
• API/database changes
• Loops/recursion in critical paths
• ORM queries added

4. Analyze code for static issues (assign prefixes):

   • SEC-: hardcoded creds, unvalidated input, SQL injection, race conditions
   • MNT-: DRY violations, dead code, complex conditionals, poor naming
   • ARCH-: layer violations, circular dependencies, guide non-compliance

5. Calculate Code Quality Score:

   • Start with 100
   • Subtract metric penalties (see Code Metrics table)
   • Subtract issue penalties (see Issue penalties table)

6. Output verdict with score and structured issues. Add Linear comment with findings.

Critical Rules

• Read guides mentioned in Story/Tasks before judging compliance.
• MCP Ref validation: For ANY architectural change, MUST verify via ref_search_documentation before judging.
• Context7 for libraries: When reviewing library usage, query-docs to verify correct patterns.
• Language preservation in comments (EN/RU).
• Do not create tasks or change statuses; caller decides next actions.

Definition of Done

• Story and Done implementation tasks loaded (test tasks excluded).
• Code metrics calculated (Cyclomatic Complexity, function/file sizes).
• MCP Ref validation completed:
  • OPT-: Optimality checked (is chosen approach the best for the goal?)
  • BP-: Best practices verified (correct implementation of chosen approach?)
  • PERF-: Performance analyzed (algorithms, configs, patterns, DB)
• Issues identified with prefixes and severity, sources from MCP Ref/Context7.
• Code Quality Score calculated.
• Output format:

  verdict: PASS | CONCERNS | ISSUES_FOUND
  code_quality_score: {0-100}
  metrics:
    avg_cyclomatic_complexity: {value}
    functions_over_50_lines: {count}
    files_over_500_lines: {count}
  issues:
    # OPTIMALITY
    - id: "OPT-001"
      severity: medium
      file: "src/auth/index.ts"
      goal: "User session management"
      finding: "Suboptimal approach for session management"
      chosen: "Custom JWT with localStorage"
      recommended: "httpOnly cookies + refresh token rotation"
      reason: "httpOnly cookies prevent XSS token theft"
      source: "ref://owasp-session-management"
  
    # BEST PRACTICES
    -  
       
       
       
       
       
  
    
      
       
       
       
       
       
       
  
    
      
       
       
       
       
       
       
  
    
      
       
       
       
       
       
       
  
    
      
       
       
       
       
  

Reference Files

• Code metrics: references/code_metrics.md (thresholds and penalties)
• Guides: docs/guides/
• Templates for context: shared/templates/task_template_implementation.md

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Version: 5.0.0 (Added 3-level MCP Ref validation: Optimality, Best Practices, Performance with PERF-ALG/CFG/PTN/DB subcategories) Last Updated: 2026-01-29