alchemist

Identify and transform high-ROI code hotspots to reduce computational complexity.

Updated Aug 23, 2026

Search Tags:#complexity #refactor #data-structures #code-optimization #algorithm-design #alchemist #complexity-ledger

Ready to run

npx skills add https://github.com/ericklemos/ai-tools --skill alchemist

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alchemist
Source: https://github.com/ericklemos/ai-tools/tree/main/.agents/skills/alchemist
Command: npx skills add https://github.com/ericklemos/ai-tools --skill alchemist

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill identifies and transforms hotspots in code with the highest ROI, pushing core algorithms and data structures toward deeper, more efficient complexity.

Core Features & Use Cases

Deep structural transformations: algorithm redesign, data-structure overhaul, and module architecture reorganization to maximize runtime reductions.
Complexity ledger discipline: requires documenting complexity targets, deltas, and trade-offs before any code changes.
Safe boundary adherence: ensures correctness and respects DDD/CQRS boundaries; changes stay within established module boundaries unless Architect approval is granted.

Quick Start

Identify the hotspot with the highest ROI in the codebase and document its Complexity Ledger before applying a deep transformational change.

Frequently Asked Questions about alchemist

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

FAQPage Schema

How do I identify and refactor high-ROI code complexity hotspots?▼

To refactor code complexity hotspots, you must first identify target areas of highest ROI and document their complexity targets and trade-offs in a Complexity Ledger before applying deep structural transformations to core algorithms.

What is a Complexity Ledger and when is it needed for code optimization?▼

A Complexity Ledger is required documentation that tracks complexity targets, deltas, and trade-offs before any code changes. It is needed when applying deep transformations like algorithm redesign or data-structure overhaul to production codebases.

Can I refactor module architecture across DDD or CQRS boundaries?▼

Refactoring module architecture must stay within established DDD or CQRS boundaries to ensure correctness. Changes across module boundaries require explicit Architect approval before structural reorganization can proceed.

How do I verify algorithm redesign correctness after deep structural changes?▼

You verify algorithm redesign correctness by running tests after applying deep structural changes. The complexity optimization process requires risk assessment and verification via tests to ensure runtime reductions are safe.

What's the best way to reduce runtime bottlenecks in core data structures?▼

The best way to reduce runtime bottlenecks is a data-structure overhaul that maximizes runtime reductions. This requires documenting trade-offs in a Complexity Ledger and respecting architectural boundaries during the transformation.