mrgoonie

simplification-cascades

@mrgoonie/simplification-cascades
mrgoonie
1,108
227 forks
Updated 1/6/2026
View on GitHub

Find one insight that eliminates multiple components - "if this is true, we don't need X, Y, or Z"

Installation

$skills install @mrgoonie/simplification-cascades
Claude Code
Cursor
Copilot
Codex
Antigravity

Details

Path.claude/skills/problem-solving/simplification-cascades/SKILL.md
Branchmain
Scoped Name@mrgoonie/simplification-cascades

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

skills list

Skill Instructions


name: Simplification Cascades description: Find one insight that eliminates multiple components - "if this is true, we don't need X, Y, or Z" when_to_use: when implementing the same concept multiple ways, accumulating special cases, or complexity is spiraling version: 1.1.0

Simplification Cascades

Overview

Sometimes one insight eliminates 10 things. Look for the unifying principle that makes multiple components unnecessary.

Core principle: "Everything is a special case of..." collapses complexity dramatically.

Quick Reference

SymptomLikely Cascade
Same thing implemented 5+ waysAbstract the common pattern
Growing special case listFind the general case
Complex rules with exceptionsFind the rule that has no exceptions
Excessive config optionsFind defaults that work for 95%

The Pattern

Look for:

  • Multiple implementations of similar concepts
  • Special case handling everywhere
  • "We need to handle A, B, C, D differently..."
  • Complex rules with many exceptions

Ask: "What if they're all the same thing underneath?"

Examples

Cascade 1: Stream Abstraction

Before: Separate handlers for batch/real-time/file/network data Insight: "All inputs are streams - just different sources" After: One stream processor, multiple stream sources Eliminated: 4 separate implementations

Cascade 2: Resource Governance

Before: Session tracking, rate limiting, file validation, connection pooling (all separate) Insight: "All are per-entity resource limits" After: One ResourceGovernor with 4 resource types Eliminated: 4 custom enforcement systems

Cascade 3: Immutability

Before: Defensive copying, locking, cache invalidation, temporal coupling Insight: "Treat everything as immutable data + transformations" After: Functional programming patterns Eliminated: Entire classes of synchronization problems

Process

  1. List the variations - What's implemented multiple ways?
  2. Find the essence - What's the same underneath?
  3. Extract abstraction - What's the domain-independent pattern?
  4. Test it - Do all cases fit cleanly?
  5. Measure cascade - How many things become unnecessary?

Red Flags You're Missing a Cascade

  • "We just need to add one more case..." (repeating forever)
  • "These are all similar but different" (maybe they're the same?)
  • Refactoring feels like whack-a-mole (fix one, break another)
  • Growing configuration file
  • "Don't touch that, it's complicated" (complexity hiding pattern)

Remember

  • Simplification cascades = 10x wins, not 10% improvements
  • One powerful abstraction > ten clever hacks
  • The pattern is usually already there, just needs recognition
  • Measure in "how many things can we delete?"

More by mrgoonie

View all
ai-multimodal
1,108

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

root-cause-tracing
1,108

Systematically trace bugs backward through call stack to find original trigger

databases
1,108

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

chrome-devtools
1,108

Browser automation, debugging, and performance analysis using Puppeteer CLI scripts. Use for automating browsers, taking screenshots, analyzing performance, monitoring network traffic, web scraping, form automation, and JavaScript debugging.