| 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)
- Load Story (full) and Done implementation tasks (full descriptions) via Linear; skip tasks with label "tests".
- Collect affected files from tasks (Affected Components/Existing Code Impact) and recent commits/diffs if noted.
- 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
-
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
-
Calculate Code Quality Score:
- Start with 100
- Subtract metric penalties (see Code Metrics table)
- Subtract issue penalties (see Issue penalties table)
-
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
Reference Files
- Code metrics:
references/code_metrics.md (thresholds and penalties)
- Guides:
docs/guides/
- Templates for context:
shared/templates/task_template_implementation.md
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
