Quality Gates Parallel (Native Multi-Agent)
Orchestrator integration for launching 4 quality subagents in parallel using Claude Code 2.1+ native Task tool with teammate coordination.
Quick Start
# Launch quality checks after implementation /quality-gates-parallel src/auth.ts --complexity 7 # Read aggregated results post-analysis /quality-gates-parallel --read-results <run_id>
Native Multi-Agent Architecture (Claude Code 2.1.16+)
Based on: claude-sneakpeek native-multiagent-gates
Features Available
- •TaskCreate: Create tasks for subagents
- •TaskUpdate: Update task status
- •TaskList: List all tasks
- •TaskGet: Get task details
- •Parallel execution: Multiple agents work independently
- •Result aggregation: Collect findings from all agents
Workflow
Phase 1: Launch Parallel Quality Checks
After implementation (orchestrator step 6b), launch 4 subagents:
// Pseudo-code for orchestrator integration 1. Classify task complexity (1-10) 2. If complexity >= 5: 3. Create 4 tasks using TaskCreate: 4. - Security auditor (sec-context-depth) 5. - Code reviewer (code-reviewer) 6. - Code cleanup (deslop) 7. - Prose cleanup (stop-slop) 8. Tasks execute in parallel (non-blocking) 9. Continue orchestrator workflow 10. Else: Skip quality checks (low complexity)
Phase 2: Read Results (Pre-Validation)
Before validation (orchestrator step 7), poll for results:
# Run results reader .claude/scripts/read-quality-results.sh <run_id>
Phase 3: Orchestrator Decision-Making
Orchestrator reads aggregated results and decides:
// Pseudo-code for decision logic
results = readQualityResults(run_id)
if (results.total_findings == 0) {
// No issues - proceed to validation
proceedToValidation()
} else if (results.critical_findings > 0) {
// Critical issues - block and fix
blockMerge()
requireFixes()
} else {
// Minor issues - advisory only
proceedWithWarnings()
}
Quality Agents (4 Parallel)
1. Security Auditor (sec-context-depth)
Agent: security-auditor or glm-reviewer
Purpose: 27 security anti-patterns (OWASP/CWE)
Findings: P0 (Critical), P1 (High), P2 (Medium)
Command: /sec-context-depth <file>
Coverage:
- •86% XSS failure rate detection
- •72% Java AI code vulnerability detection
- •SQL injection, command injection, XSS
- •JWT none algorithm, weak hashing, ECB mode
2. Code Reviewer (code-reviewer)
Agent: code-reviewer or codex-cli
Purpose: Official Claude Code plugin with 4 parallel agents
Features: Confidence scoring (≥80 threshold)
Command: /code-review <file>
Architecture:
- •Agent #1: CLAUDE.md compliance
- •Agent #2: CLAUDE.md compliance (redundancy)
- •Agent #3: Bug detection (changes only)
- •Agent #4: Git blame/history analysis
3. Code Cleanup (deslop)
Agent: refactorer or gemini-cli
Purpose: Remove AI-generated code slop
Command: /deslop
Removes:
- •Extra comments inconsistent with codebase
- •Extra defensive checks/try/catch blocks
- •Casts to
anyfor type issues - •Inline imports (move to top)
4. Prose Cleanup (stop-slop)
Agent: docs-writer or minimax
Purpose: Remove AI writing patterns from prose
Command: /stop-slop <file>
Removes:
- •Filler phrases ("Certainly!", "It is important to note")
- •Structural clichés (binary contrasts, dramatic fragmentation)
- •Stylistic habits (tripling, metronomic endings)
Integration with Orchestrator
Step 6b.5: Quality Parallel (NEW)
Location: After implementation (6b), before validation (7)
Trigger: complexity >= 5 OR security-related code
Execution:
# Non-blocking parallel launch .claude/scripts/quality-coordinator.sh <target_file> <complexity>
Output: JSON with 4 task definitions
Step 7: Validation with Quality Results
Before validation: Read aggregated results
# Poll for completed checks .claude/scripts/read-quality-results.sh <run_id>
Output: Aggregated JSON with all findings
Decision Logic:
- •0 findings: Proceed to validation
- •Critical findings: Block and require fixes
- •Minor findings: Advisory warnings
Results Storage
.claude/quality-results/ ├── aggregated_<run_id>.json # Aggregated results ├── sec-context_<run_id>.json # Security findings ├── code-review_<run_id>.json # Code review findings ├── deslop_<run_id>.json # Code cleanup findings ├── stop-slop_<run_id>.json # Prose cleanup findings ├── *_<run_id>.done # Completion markers └── coordinator.log # Execution log
Usage Examples
Manual Execution
# Launch quality checks ./.claude/scripts/quality-coordinator.sh src/auth.ts 7 # Read results ./.claude/scripts/read-quality-results.sh 20250128_221437_12345
Orchestrator Integration
# In orchestrator step 6b (after implementation)
quality_check_result=$(./.claude/scripts/quality-coordinator.sh "$file" "$complexity")
# Parse result and create tasks
if [[ "$complexity" -ge 5 ]]; then
# Create 4 tasks using TaskCreate
# Tasks execute in parallel
# Store run_id for later retrieval
fi
# In orchestrator step 7 (before validation)
quality_results=$(./.claude/scripts/read-quality-results.sh "$run_id")
# Parse results and make decision
critical_count=$(echo "$quality_results" | jq '.summary.critical_findings // 0')
if [[ "$critical_count" -gt 0 ]]; then
# Block and require fixes
echo "CRITICAL: $critical_count security issues found"
else
# Proceed to validation
echo "No critical issues, proceeding to validation"
fi
Scripts
- •quality-coordinator.sh: Launch 4 quality tasks in parallel
- •read-quality-results.sh: Poll and aggregate results
Hooks
- •quality-parallel-async.sh: Async hook for Edit/Write operations
- •Uses
async: truein settings.json - •Non-blocking background execution
- •Results stored for later reading
- •Uses
Version History
- •1.0.0 (2026-01-28): Initial native multi-agent integration
- •Based on Claude Code 2.1.16+ Task tool
- •4 parallel quality agents
- •Result aggregation and polling
References
- •Native Multi-Agent Gates: claude-sneakpeek documentation
- •Claude Code 2.1.16+ features: Swarms, TeammateTool, teammate coordination
- •Quality consolidation:
docs/analysis/QUALITY_PARALLEL_CONSOLIDATION_v2.80.3.md - •Async hooks correction:
docs/analysis/ASYNC_HOOKS_CORRECTION_v2.80.2.md