legacy-modernizer
Designs incremental migration strategies, identifies service boundaries, produces dependency maps and migration roadmaps, and generates API facade designs for aging codebases. Use when modernizing legacy systems, implementing strangler fig pattern or branch by abstraction, decomposing monoliths, upgrading frameworks or languages, or reducing technical debt without disrupting business operations.
git clone --depth 1 https://github.com/Jeffallan/claude-skills /tmp/legacy-modernizer && cp -r /tmp/legacy-modernizer/skills/legacy-modernizer ~/.claude/skills/legacy-modernizerSKILL.md
# Legacy Modernizer
## Core Workflow
1. **Assess system** — Analyze codebase, dependencies, risks, and business constraints. Produce a dependency map and risk register before proceeding.
- *Validation checkpoint:* Confirm all external integrations and data contracts are documented before moving to step 2.
2. **Plan migration** — Design an incremental roadmap with explicit rollback strategies per phase. Reference `references/system-assessment.md` for code analysis templates.
- *Validation checkpoint:* Confirm each phase has a defined rollback trigger and owner.
3. **Build safety net** — Create characterization tests and monitoring before touching production code. Target 80%+ coverage of existing behavior.
- *Validation checkpoint:* Run the characterization test suite and confirm it passes green on the unmodified legacy system before proceeding.
4. **Migrate incrementally** — Apply strangler fig pattern with feature flags. Route traffic via a facade; shift load gradually.
- *Validation checkpoint:* Verify error rates and latency metrics remain within baseline thresholds after each traffic increment (e.g., 5% → 25% → 50% → 100%).
5. **Validate & iterate** — Run full test suite, review monitoring dashboards, and confirm business behavior is preserved before retiring legacy code.
- *Validation checkpoint:* New code must be proven stable at 100% traffic for at least one release cycle before legacy path is removed.
## Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|-------|-----------|-----------|
| Strangler Fig | `references/strangler-fig-pattern.md` | Incremental replacement, facade layer, routing |
| Refactoring | `references/refactoring-patterns.md` | Extract service, branch by abstraction, adapters |
| Migration | `references/migration-strategies.md` | Database, UI, API, framework migrations |
| Testing | `references/legacy-testing.md` | Characterization tests, golden master, approval |
| Assessment | `references/system-assessment.md` | Code analysis, dependency mapping, risk evaluation |
## Code Examples
### Strangler Fig Facade (Python)
```python
# facade.py — routes requests to legacy or new service based on a feature flag
import os
from legacy_service import LegacyOrderService
from new_service import NewOrderService
class OrderServiceFacade:
def __init__(self):
self._legacy = LegacyOrderService()
self._new = NewOrderService()
def get_order(self, order_id: str):
if os.getenv("USE_NEW_ORDER_SERVICE", "false").lower() == "true":
return self._new.fetch(order_id)
return self._legacy.get(order_id)
```
### Feature Flag Wrapper
```python
# feature_flags.py — thin wrapper around an environment or config-based flag store
import os
def flag_enabled(flag_name: str, default: bool = False) -> bool:
"""Check whether a migration feature flag is active."""
return os.getenv(flag_name, str(default)).lower() == "true"
# Usage
if flag_enabled("USE_NEW_PAYMENT_GATEWAY"):
result = new_gateway.charge(order)
else:
result = legacy_gateway.charge(order)
```
### Characterization Test Template (pytest)
```python
# test_characterization_orders.py
# Captures existing legacy behavior as a golden-master safety net.
import pytest
from legacy_service import LegacyOrderService
service = LegacyOrderService()
@pytest.mark.parametrize("order_id,expected_status", [
("ORD-001", "SHIPPED"),
("ORD-002", "PENDING"),
("ORD-003", "CANCELLED"),
])
def test_order_status_golden_master(order_id, expected_status):
"""Fail loudly if legacy behavior changes unexpectedly."""
result = service.get(order_id)
assert result["status"] == expected_status, (
f"Characterization broken for {order_id}: "
f"expected {expected_status}, got {result['status']}"
)
```
## Constraints
### MUST DO
- Maintain zero production disruption during all migrations
- Create comprehensive test coverage before refactoring (target 80%+)
- Use feature flags for all incremental rollouts
- Implement monitoring and rollback procedures
- Document all migration decisions and rationale
- Preserve existing business logic and behavior
- Communicate progress and risks transparently
### MUST NOT DO
- Big bang rewrites or replacements
- Skip testing legacy behavior before changes
- Deploy without rollback capability
- Break existing integrations or APIs
- Ignore technical debt in new code
- Rush migrations without proper validation
- Remove legacy code before new code is proven
## Output Templates
When implementing modernization, provide:
1. Assessment summary (risks, dependencies, approach)
2. Migration plan (phases, rollback strategy, metrics)
3. Implementation code (facades, adapters, new services)
4. Test coverage (characterization, integration, e2e)
5. Monitoring setup (metrics, alerts, dashboards)
## Knowledge Reference
Strangler fig pattern, branch by abstraction, characterization testing, incremental migration, feature flags, canary deployments, API versioning, database refactoring, microservices extraction, technical debt reduction, zero-downtime deployment
[Documentation](https://jeffallan.github.io/claude-skills/skills/specialized/legacy-modernizer/)Generates Angular 17+ standalone components, configures advanced routing with lazy loading and guards, implements NgRx state management, applies RxJS patterns, and optimizes bundle performance. Use when building Angular 17+ applications with standalone components or signals, setting up NgRx stores, establishing RxJS reactive patterns, performance tuning, or writing Angular tests for enterprise apps.
Use when designing REST or GraphQL APIs, creating OpenAPI specifications, or planning API architecture. Invoke for resource modeling, versioning strategies, pagination patterns, error handling standards.
Use when designing new high-level system architecture, reviewing existing designs, or making architectural decisions. Invoke to create architecture diagrams, write Architecture Decision Records (ADRs), evaluate technology trade-offs, design component interactions, and plan for scalability. Use for system design, architecture review, microservices structuring, ADR authoring, scalability planning, and infrastructure pattern selection — distinct from code-level design patterns or database-only design tasks.
Integrates with Atlassian products to manage project tracking and documentation via MCP protocol. Use when querying Jira issues with JQL filters, creating and updating tickets with custom fields, searching or editing Confluence pages with CQL, managing sprints and backlogs, setting up MCP server authentication, syncing documentation, or debugging Atlassian API integrations.
Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post-mortem templates. Use when designing chaos experiments, implementing failure injection frameworks, or conducting game day exercises. Invoke for chaos experiments, resilience testing, blast radius control, game days, antifragile systems, fault injection, Chaos Monkey, Litmus Chaos.
Use when building CLI tools, implementing argument parsing, or adding interactive prompts. Invoke for parsing flags and subcommands, displaying progress bars and spinners, generating bash/zsh/fish completion scripts, CLI design, shell completions, and cross-platform terminal applications using commander, click, typer, or cobra.
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost optimization, disaster recovery, landing zones, security architecture, serverless design.
Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides. Use when adding docstrings to functions or classes, creating API documentation, building documentation sites, or writing tutorials and user guides. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, getting started guides.