modu-ai Development Workflow Specialist
Quick Reference
Unified development workflow combining DDD (domain-driven development) testing, debugging guidance, performance optimization, automated code review, and CI/CD quality gates. Emphasizes behavior preservation during refactoring through characterization tests.
Core Capabilities:
- DDD Testing: Characterization tests (legacy) + specification tests (greenfield) + behavior snapshots
- AI-Powered Debugging: Error analysis, classification, solution candidates
- Performance Optimization: Profiling, bottleneck detection, optimization recommendations
- Automated Code Review: TRUST 5 framework validation
- PR Code Review: Multi-agent pattern (Haiku eligibility + 5 Sonnet parallel reviewers)
- Quality Assurance: CI/CD integration with quality gates
Workflow Progression: Debug → Refactor → Optimize → Review → Test → Profile
When to Use:
- Complete development lifecycle management
- Quality assurance and CI/CD integration
- Multi-language and performance-critical projects
- Technical debt reduction
- PR code review automation
Implementation Guide
Core Concepts
Five integrated components form the workflow:
- AI-Powered Debugging: Error classification (syntax/runtime/logic/integration/performance) and solution candidates ranked by likelihood
- Smart Refactoring: Technical debt analysis with complexity metrics and risk assessment
- Performance Optimization: CPU/memory/IO/network profiling with optimization strategies
- DDD Testing Management: Characterization tests (PRESERVE phase) for legacy + specification tests for greenfield + TRUST 5 validation
- Automated Code Review: TRUST 5 framework with actionable recommendations
TRUST 5 Framework
Quality assessment model with five dimensions:
- Testability: pure functions, injectable dependencies, modular design
- Readability: descriptive names, logical structure, documented complexity
- Understandability: clear business logic, appropriate abstractions, conceptual clarity
- Security: input validation, secret management, OWASP compliance (injection/XSS/CSRF)
- Transparency: comprehensive error handling, structured logs, traceable issues
Overall score: weighted average with critical-dimension override (security/testability cannot be masked).
See TRUST 5 detailed dimensions and scoring for full assessment rubric.
DDD Testing Process
Legacy Code (PRESERVE phase):
- Write characterization tests documenting current behavior (not aspirational)
- Organize tests by domain concepts to surface domain boundaries
- Use behavior snapshots as regression safeguards for complex scenarios
- Verify baseline: all characterization tests PASS before any change
- Apply refactoring with continuous test execution
- Run TRUST 5 validation post-refactor
Greenfield Development:
- Derive specification tests from domain requirements (each test = business rule)
- Organize tests by aggregates, entities, value objects (DDD ubiquitous language)
- Specify behavior in business language, not implementation details
- Implement to satisfy specifications
- Verify with integration tests (domain interactions + invariants)
- Apply TRUST 5 validation
Debugging, Refactoring, Performance Workflows
All three follow a 6-step pattern: capture/analyze → classify → identify candidates → apply → verify → document.
See debugging/refactoring/performance step-by-step walkthroughs for detailed process tables.
Code Review Process
- Scan codebase for review targets
- Apply TRUST 5 framework per file
- Identify critical issues
- Calculate per-file + aggregate scores
- Generate prioritized recommendations
- Create summary report with improvement roadmap
PR Code Review (Multi-Agent Pattern)
5-step multi-agent pipeline:
- Eligibility Check (Haiku): skip closed/draft/already-reviewed/trivial PRs
- Context Gathering: find CLAUDE.md per modified dir + summarize PR
- Parallel Review (5 Sonnet agents): CLAUDE.md compliance / obvious bugs / git blame / previous comments / code comment compliance
- Confidence Scoring (0-100): 0=false positive, 25=somewhat, 50=moderate, 75=high, 100=certain
- Filter & Report: drop issues <80 confidence, post via gh CLI with file/line/commit links
See PR review multi-agent architecture and output format for agent role detail and example output.
Multi-Language Support
Per-language toolchain mappings (Python pytest+ruff+bandit, JS/TS Jest+ESLint+npm audit, Go go test+staticcheck+gosec, Rust cargo test+clippy+gosec equivalents).
See multi-language toolchain reference for per-language testing/lint/security/perf tool inventory.
Advanced Features
Quality Gate Configuration
Three strictness modes:
- Strict: all TRUST dimensions ≥ threshold, zero critical issues, full coverage
- Standard: average score ≥ threshold, no critical issues blocking, warnings allowed
- Lenient: only critical blockers prevent progression
Gate config: per-dimension thresholds, max issues by severity, coverage targets, perf benchmarks.
CI/CD Integration
Four-stage pipeline: Code Quality → Testing → Performance → Security. Each stage terminates pipeline on failure with stage-specific failure report.
See CI/CD integration patterns (GitHub Actions + Docker) for job configuration walkthroughs.
E2E / Browser Testing
Playwright patterns (Page Object Model, cross-browser, visual regression) and documentation-lookup integration. See Playwright best practices.
Modules
Deep-dive modules for each workflow stage. These describe conceptual workflows (not an importable SDK) — apply each with your project's own toolchain. Start at the modules index, or jump to a stage:
- AI-Powered Debugging — error classification + solution candidates
- Smart Refactoring — technical-debt analysis + safe transforms
- Performance Optimization — profiling + bottleneck detection
- Automated Code Review — TRUST 5 scoring + static analysis
Works Well With
- moai-domain-backend: Backend testing patterns
- moai-domain-frontend: Frontend UI testing
- moai-foundation-core: SPEC system integration
- moai-platform-supabase / moai-platform-vercel / moai-platform-firebase-auth: Platform-specific testing
- moai-workflow-project: Project management workflows
Status: Production Ready Last Updated: 2026-07-10 Maintained by: MoAI-ADK Development Workflow Team Version: 2.5.0 (audit remediation: language-neutrality + module re-linking)
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "This code is already covered by integration tests" | Integration tests catch different bugs than unit tests. The testing pyramid exists for a reason. |
| "Mocking the database is too hard, I will skip that test" | If the test is hard to write because of coupling, the code needs a better abstraction boundary. |
| "80% coverage is good enough" | Coverage targets are floors, not ceilings. The missing 20% often contains the error handling paths. |
| "These are just utility functions, they do not need tests" | Utility functions are the most reused code. A bug in a utility propagates everywhere. |
| "I ran the tests locally, CI will pass" | Environment differences cause CI-only failures. Trust CI output, not local runs. |
| "Flaky tests are normal, just re-run" | Flaky tests hide real failures. Fix the flakiness or quarantine the test explicitly. |
Shift Left: Find and fix defects as early as possible. Every test that runs in CI instead of locally adds latency. Every test that could have been a unit test but is an E2E test adds fragility.
Beyonce Rule: If you liked it, you should have put a test on it. Untested behavior is unspecified behavior.
Red Flags
- Coverage report shows decreased coverage after a feature addition
- Test file contains
t.Skip()orskipwithout an accompanying issue tracker link - Test names are auto-generated (test_1, test_2) instead of behavior-descriptive
- No test touches the error/failure branch of a new function
- Test file imports the concrete implementation instead of the interface
Verification
- Test suite passes with zero failures (paste command output)
- Coverage report generated and meets the 85% threshold for changed packages
- Error paths have dedicated test cases (not just happy path)
- No flaky tests introduced (run with -count=3 to verify stability)
- Test isolation confirmed: each test uses its own fixtures or t.TempDir()
- Race detector passed for concurrent code (go test -race or equivalent)