levelup-init

Scan brownfield codebases to generate Context Directive Records.

Updated Jul 7, 2026
One-click install
npx skills add https://github.com/eavichay/mycli --skill levelup-init-eavichay
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: levelup-init
Source: https://github.com/eavichay/mycli/tree/main/.cursor/skills/levelup-init
Command: npx skills add https://github.com/eavichay/mycli --skill levelup-init-eavichay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill solves the challenge of maintaining consistent coding standards and governance across large, multi-sub-system codebases by automating the discovery of patterns and the generation of Context Directive Records (CDRs).

Core Features & Use Cases

  • Multi-Agent Analysis: Orchestrates specialized agents for discovery, pattern classification, and synthesis to ensure comprehensive codebase coverage.
  • Cross-Sub-System Detection: Identifies patterns and inconsistencies across different modules, flagging them for team review.
  • Constitution Generation: Automatically derives governance principles from codebase evidence to bootstrap or amend your team's constitution.

Quick Start

Run the levelup-init skill to scan the current repository and generate context directive records for team-ai-directives.

Frequently Asked Questions about levelup-init

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

FAQPage Schema
How do I automate codebase analysis for team-ai-directives in a brownfield project?

Automate codebase analysis for team-ai-directives by running a multi-agent pipeline that scans brownfield codebases to discover reusable patterns and generate Context Directive Records.

How do I detect cross-sub-system inconsistencies in a monorepo architecture?

Detect cross-sub-system inconsistencies in a monorepo architecture using specialized agents that identify patterns and flag inconsistencies across different modules for team review.

Can I automatically generate a governance constitution from existing codebase evidence?

You can automatically generate a governance constitution from codebase evidence by synthesizing discovered patterns to bootstrap or amend your team's governance principles.

Does this multi-agent codebase analysis work with multi-sub-system architectures?

This multi-agent codebase analysis explicitly applies to monorepo and multi-sub-system architectures, satisfying requirements for state persistence and cross-sub-system inconsistency detection.

What is the best way to standardize coding standards across large codebases?

The best way to standardize coding standards across large codebases is automating pattern discovery and Context Directive Record generation to maintain consistent governance.

Why does cross-sub-system pattern discovery require a multi-agent pipeline?

Cross-sub-system pattern discovery requires a multi-agent pipeline because orchestrating specialized agents for discovery, classification, and synthesis ensures comprehensive codebase coverage.