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name: reverse-engineer description: Deep codebase analysis to generate 9 comprehensive documentation files. Adapts based on path choice - Greenfield extracts business logic only (tech-agnostic), Brownfield extracts business logic + technical implementation (tech-prescriptive). This is Step 2 of 6 in the reverse engineering process.

Reverse Engineer (Path-Aware)

Step 2 of 6 in the Reverse Engineering to Spec-Driven Development process.

Estimated Time: 30-45 minutes Prerequisites: Step 1 completed (analysis-report.md and path selection) Output: 9 comprehensive documentation files in docs/reverse-engineering/

Path-Dependent Behavior:

• Greenfield: Extract business logic only (framework-agnostic)
• Brownfield: Extract business logic + technical implementation details

Note: Output is the same regardless of implementation framework (Spec Kit or BMAD). The framework choice only affects what happens at Gear 6 (handoff).

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When to Use This Skill

Use this skill when:

• You've completed Step 1 (Initial Analysis) with path selection
• Ready to extract comprehensive documentation from code
• Path has been chosen (greenfield or brownfield)
• Preparing to create formal specifications

Trigger Phrases:

• "Reverse engineer the codebase"
• "Generate comprehensive documentation"
• "Extract business logic" (greenfield)
• "Document the full implementation" (brownfield)

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What This Skill Does

This skill performs deep codebase analysis and generates 9 comprehensive documentation files.

Content adapts based on your route (greenfield vs brownfield):

Path A: Greenfield (Business Logic Only)

• Focus on WHAT the system does
• Avoid framework/technology specifics
• Extract user stories, business rules, workflows
• Framework-agnostic functional requirements
• Can be implemented in any tech stack

Path B: Brownfield (Business Logic + Technical)

• Focus on WHAT and HOW
• Document exact frameworks, libraries, versions
• Extract file paths, configurations, schemas
• Prescriptive technical requirements
• Enables /speckit.analyze validation

9 Documentation Files Generated:

1. functional-specification.md - Business logic, requirements, user stories (+ tech details for brownfield)
2. integration-points.md - External services, APIs, dependencies, data flows (single source of truth)
3. configuration-reference.md - Config options (business-level for greenfield, all details for brownfield)
4. data-architecture.md - Data models, API contracts (abstract for greenfield, schemas for brownfield)
5. operations-guide.md - Operational needs (requirements for greenfield, current setup for brownfield)
6. technical-debt-analysis.md - Issues and improvements
7. observability-requirements.md - Monitoring needs (goals for greenfield, current state for brownfield)
8. visual-design-system.md - UI/UX patterns (requirements for greenfield, implementation for brownfield)
9. test-documentation.md - Testing requirements (targets for greenfield, current state for brownfield)

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Configuration Check (FIRST STEP!)

Load state file to check detection type and route:

Copy# Check what kind of application we're analyzing
DETECTION_TYPE=$(cat .stackshift-state.json | jq -r '.detection_type // .path')
echo "Detection: $DETECTION_TYPE"

# Check extraction approach
ROUTE=$(cat .stackshift-state.json | jq -r '.route // .path')
echo "Route: $ROUTE"

# Check spec output location (Greenfield only)
SPEC_OUTPUT=$(cat .stackshift-state.json | jq -r '.config.spec_output_location // "."')
echo "Writing specs to: $SPEC_OUTPUT"

# Create output directories if needed
if [ "$SPEC_OUTPUT" != "." ]; then
  mkdir -p "$SPEC_OUTPUT/docs/reverse-engineering"
  mkdir -p "$SPEC_OUTPUT/.specify/memory/specifications"
fi

State file structure:

Copy{
  "detection_type": "monorepo-service",  // What kind of app
  "route": "greenfield",                  // How to spec it
  "implementation_framework": "speckit",  // speckit or bmad (affects Gear 6 only)
  "config": {
    "spec_output_location": "~/git/my-new-app",
    "build_location": "~/git/my-new-app",
    "target_stack": "Next.js 15..."
  }
}

Output structure (same for all frameworks):

Copydocs/reverse-engineering/
├── functional-specification.md
├── integration-points.md
├── configuration-reference.md
├── data-architecture.md
├── operations-guide.md
├── technical-debt-analysis.md
├── observability-requirements.md
├── visual-design-system.md
└── test-documentation.md

Extraction approach based on detection + route:

How it works:

• detection_type determines WHAT patterns to look for (shared packages, Nx project config, monorepo structure, etc.)
• route determines HOW to document them (tech-agnostic vs tech-prescriptive)

Examples:

• Monorepo Service + Greenfield → Extract what the service does (not React/Express specifics)
• Monorepo Service + Brownfield → Extract full Express routes, React components, shared utilities
• Nx App + Greenfield → Extract business logic (not Angular specifics)
• Nx App + Brownfield → Extract full Nx configuration, Angular components, project graph

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Process Overview

Phase 1: Deep Codebase Analysis

Approach depends on path:

Use the Task tool with subagent_type=stackshift:code-analyzer (or Explore as fallback) to analyze:

1.1 Backend Analysis

• All API endpoints (method, path, auth, params, purpose)
• Data models (schemas, types, interfaces, fields)
• Configuration (env vars, config files, settings)
• External integrations (APIs, services, databases)
• Business logic (services, utilities, algorithms)

See operations/backend-analysis.md

1.2 Frontend Analysis

• All pages/routes (path, purpose, auth requirement)
• Components catalog (layout, form, UI components)
• State management (store structure, global state)
• API client (how frontend calls backend)
• Styling (design system, themes, component styles)

See operations/frontend-analysis.md

1.3 Infrastructure Analysis

• Deployment (IaC tools, configuration)
• CI/CD (pipelines, workflows)
• Hosting (cloud provider, services)
• Database (type, schema, migrations)
• Storage (object storage, file systems)

See operations/infrastructure-analysis.md

1.4 Testing Analysis

• Test files (location, framework, coverage)
• Test types (unit, integration, E2E)
• Coverage estimates (% covered)
• Test data (mocks, fixtures, seeds)

See operations/testing-analysis.md

Phase 2: Generate Documentation

Create docs/reverse-engineering/ directory and generate all 8 documentation files.

See operations/generate-docs.md for templates and guidelines.

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Output Files

All 9 documentation files are written to docs/reverse-engineering/ regardless of implementation framework choice.

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1. functional-specification.md

Focus: Business logic, WHAT the system does (not HOW)

Sections:

• Executive Summary (purpose, users, value)
• Functional Requirements (FR-001, FR-002, ...)
• User Stories (P0/P1/P2/P3 priorities)
• Non-Functional Requirements (NFR-001, ...)
• Business Rules (validation, authorization, workflows)
• System Boundaries (scope, integrations)
• Success Criteria (measurable outcomes)

Critical: Framework-agnostic, testable, measurable

2. configuration-reference.md

Complete inventory of all configuration:

• Environment variables
• Config file options
• Feature flags
• Secrets and credentials (how managed)
• Default values

3. data-architecture.md

All data models and API contracts:

• Data models (with field types, constraints, relationships)
• API endpoints (request/response formats)
• JSON Schemas
• GraphQL schemas (if applicable)
• Database ER diagram (textual)

4. operations-guide.md

How to deploy and maintain:

• Deployment procedures
• Infrastructure overview
• Monitoring and alerting
• Backup and recovery
• Troubleshooting runbooks

5. technical-debt-analysis.md

Issues and improvements:

• Code quality issues
• Missing tests
• Security vulnerabilities
• Performance bottlenecks
• Refactoring opportunities

6. observability-requirements.md

Logging, monitoring, alerting:

• What to log (events, errors, metrics)
• Monitoring requirements (uptime, latency, errors)
• Alerting rules and thresholds
• Debugging capabilities

7. visual-design-system.md

UI/UX patterns:

• Component library
• Design tokens (colors, typography, spacing)
• Responsive breakpoints
• Accessibility standards
• User flows

8. test-documentation.md

Testing requirements:

• Test strategy
• Coverage requirements
• Test patterns and conventions
• E2E scenarios
• Performance testing

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Success Criteria

• ✅ docs/reverse-engineering/ directory created
• ✅ All 9 documentation files generated
• ✅ Comprehensive coverage of all application aspects
• ✅ Framework-agnostic functional specification (for greenfield)
• ✅ Complete data model documentation
• ✅ Ready to proceed to Step 3 (Create Specifications)

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Next Step

Once all documentation is generated and reviewed:

For GitHub Spec Kit (implementation_framework: speckit):

• Proceed to Step 3: Create Specifications - Use /stackshift.create-specs to transform docs into .specify/ specs

For BMAD Method (implementation_framework: bmad):

• Proceed to Step 6: Implementation which will hand off to BMAD's *workflow-init
• BMAD's PM and Architect agents will use the reverse-engineering docs as rich context
• They will collaboratively create the PRD and architecture through conversation

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Important Guidelines

Framework-Agnostic Documentation

DO:

• Describe WHAT, not HOW
• Focus on business logic and requirements
• Use generic terms (e.g., "HTTP API" not "Express routes")

DON'T:

• Hard-code framework names in functional specs
• Describe implementation details in requirements
• Mix business logic with technical implementation

Completeness

Use the Explore agent to ensure you find:

• ALL API endpoints (not just the obvious ones)
• ALL data models (including DTOs, types, interfaces)
• ALL configuration options (check multiple files)
• ALL external integrations

Quality Standards

Each document must be:

• Comprehensive - Nothing important missing
• Accurate - Reflects actual code, not assumptions
• Organized - Clear sections, easy to navigate
• Actionable - Can be used to rebuild the system

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Technical Notes

• Use Task tool with subagent_type=stackshift:code-analyzer for path-aware extraction
• Fallback to subagent_type=Explore if StackShift agent not available
• Parallel analysis: Run backend, frontend, infrastructure analysis concurrently
• Use multiple rounds of exploration for complex codebases
• Cross-reference findings across different parts of the codebase
• The stackshift:code-analyzer agent understands greenfield vs brownfield routes automatically

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Remember: This is Step 2 of 6. The documentation you generate here will be transformed into formal specifications in Step 3.