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legacy-modernizer

Designs incremental migration strategies, identifies service boundaries, produces dependency maps and migration roadmaps, and generates API facade designs for aging codebases

Install / Use

npx skills add Jeffallan/claude-skills --skill legacy-modernizer

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

94/100

Supported Platforms

Zed

Our assessment of legacy-modernizer

legacy-modernizer scores 94/100 on our quality scale, 4th of 42 Product Management skills we index (top 10%).

Its SKILL.md is 5.9 KB long, well organised into 17 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

With 11,621 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
18/20
Description
15/15
Adoption
17/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so legacy-modernizer is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

legacy-modernizer compared with similar skills

All 4 of these similar skills score higher than legacy-modernizer; compare them before choosing.

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legacy-modernizer (this skill)by Jeffallan9411.6k51d agoSKILL.md
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crawl4aiby unclecode10084.4k2d agoMCP Server
Scraplingby D4Vinci10084.1ktodayMCP Server

Frequently asked questions

How do I install legacy-modernizer?
Run npx skills add Jeffallan/claude-skills --skill legacy-modernizer. The install tabs above show the steps for each supported agent.
Which AI agents does legacy-modernizer work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is legacy-modernizer safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is legacy-modernizer still maintained?
The repository was last updated about 2 months ago, so legacy-modernizer is actively maintained.

name: legacy-modernizer description: 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. license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: specialized triggers: legacy modernization, strangler fig, incremental migration, technical debt, legacy refactoring, system migration, legacy system, modernize codebase role: specialist scope: architecture output-format: code+analysis related-skills: test-master, devops-engineer

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)

# 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

# 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)

# 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

Related Skills

View on GitHub
GitHub Stars11.6k
CategoryProduct
Updated1mo ago
Forks1.1k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions