nuclear-review

Reviews code changes for structural regressions, file-size growth, and spaghetti branching.

1|Updated Mar 27, 2026
One-click install
npx skills add https://github.com/lrstanley/skills --skill nuclear-review-lrstanley
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nuclear-review
Source: https://github.com/lrstanley/skills/tree/main/nuclear-review
Command: npx skills add https://github.com/lrstanley/skills --skill nuclear-review-lrstanley

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Standard code reviews often rubber-stamp working code that quietly degrades maintainability through sprawling files, ad-hoc conditionals, and unnecessary abstractions. This Skill enforces an unusually strict review standard focused on structural quality and long-term codebase health. ## Core Features & Use Cases - Structural Regression Detection: Flags PRs that push files past 1000 lines, add scattered special-case branching, or leak feature logic into shared modules. - Code-Judo Restructuring Suggestions: Actively searches for reframings that delete entire layers of complexity rather than merely rearranging them. - Strict Approval Bar: Blocks approval when changes introduce thin wrappers, cast-heavy contracts, duplicated helpers, or non-atomic update flows without justification. - Use Case: Before merging a large feature branch, run this review to catch maintainability debt early and get concrete refactoring suggestions like extracting helpers, splitting modules, or simplifying state models. ## Quick Start Run a thermo-nuclear code quality review on the current branch's changes and flag any structural regressions.

Frequently Asked Questions about nuclear-review

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

FAQPage Schema
How do I run a strict code quality review on a pull request?▼

Invoke this review on the current branch's changes to audit abstraction quality, file size, and branching complexity. It produces prioritized findings with concrete restructuring suggestions rather than surface-level style comments.

What does a maintainability-focused code review check for?▼

It checks for files crossing 1000 lines, ad-hoc conditionals added to unrelated flows, thin wrapper abstractions, cast-heavy type boundaries, logic in the wrong layer, and non-atomic update patterns. Each finding includes a preferred remedy.

When should I use a deep code audit instead of a standard review?▼

Use it for large feature branches, refactors, or changes touching shared modules where structural debt is likely. Standard reviews catch bugs; this audit catches design decisions that make the codebase harder to maintain over time.

What are the limitations of an automated maintainability review?▼

It evaluates structural quality heuristics like file size and branching patterns, which require human judgment to override when justified. It does not verify runtime correctness, performance, or test coverage.

Can this review block a pull request from being approved?▼

Yes, it treats unjustified file-size explosions, spaghetti branching, unnecessary abstractions, and missed decomposition opportunities as presumptive blockers. Authors must justify these patterns or restructure before approval.