hatch3r-logical-refactor

Plan and implement logical refactors while preserving invariants with tests.

26|4|Updated Feb 27, 2026
One-click install
npx skills add https://github.com/hatch3r/hatch3r --skill hatch3r-logical-refactor
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hatch3r-logical-refactor
Source: https://github.com/hatch3r/hatch3r/tree/main/skills/hatch3r-logical-refactor
Command: npx skills add https://github.com/hatch3r/hatch3r --skill hatch3r-logical-refactor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Logical refactors often risk unintentionally changing behavior, breaking invariants, or expanding scope beyond the intended fix; this workflow helps you update behavior while preserving what must not change.

Core Features & Use Cases

  • Ambiguity detection with explicit clarification: flags unresolved acceptance criteria, invariants, environment constraints, and scope irreversibility before editing.
  • Change-plan first, then implementation: requires a before/after definition, preserved vs changed invariants, files to modify, and risks before touching code.
  • Test-driven safety for behavior equivalence: updates, adds, and verifies regression and characterization tests to ensure preserved invariants remain true.
  • Scope control and PR-ready evidence: stops or escalates when the refactor grows, and packages before/after behavior plus test evidence for review.
  • Quality guardrails: enforces fan-out discipline for multi-file/high-risk changes and maintains efficiency via the skill’s orchestration outputs.

Quick Start

Use the hatch3r logical refactor workflow to update business logic safely by asking the AI to execute the full refactor plan for your issue and validate invariants with updated and added tests.

Frequently Asked Questions about hatch3r-logical-refactor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I safely refactor business logic without changing existing behavior?

Logical refactoring requires documenting a change plan that separates preserved invariants from changed ones before modifying any code. You must detect ambiguities, define before/after behavior, and verify safety using regression and characterization tests.

What is the best way to prepare a PR for a complex data-flow modification?

The best way to prepare a PR for a data-flow modification is to package before/after behavior definitions alongside explicit test evidence. This documents preserved versus changed invariants, ensuring reviewers can validate scope and downstream impact.

How do I check if a logic change will break downstream dependencies before editing?

To check if a logic change breaks downstream dependencies, assess downstream impact and detect scope irreversibility during the planning phase. Ambiguity detection flags unresolved environment constraints and acceptance criteria before code editing begins.

When do I need characterization tests for a code refactor?

You need characterization tests for a code refactor when existing test coverage is insufficient to verify behavior equivalence. They capture current behavior as invariants, ensuring your logical refactor does not unintentionally change required data-flow outputs.

What should I do if my logical refactor expands beyond the intended scope?

If your logical refactor expands beyond the intended scope, stop or escalate the code orchestration to maintain fan-out discipline. Scope control prevents multi-file and high-risk changes from growing beyond the original approved behavior modification.