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lessons

Analyze git history to identify patterns and generate monetizable playbooks.

Updated May 1, 2026
Search Tags:#project management#code review#hypothesis testing#portfolio analysis#AI-paired workflow
One-click install
npx skills add https://github.com/ereztash/lessons --skill lessons-ereztash
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lessons
Source: https://github.com/ereztash/lessons/tree/main
Command: npx skills add https://github.com/ereztash/lessons --skill lessons-ereztash

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mcp__github__*, Octokit, Supabase, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive framework for optimizing AI-paired workflows, addressing the challenges of project management, code review, and personal workflow improvement for solo builders and small teams.

Core Features & Use Cases

  • Workflow Analysis: Deep dive into the git history of projects to identify patterns and anti-patterns.
  • Monetization Gate: Ensures insights are actionable and valuable for the target audience.
  • Playbook Generation: Offers ready-to-use playbooks for common AI-paired workflow challenges.
  • Portfolio Analysis: Evaluates the health and maturity of a portfolio of AI-paired projects.
  • Hypothesis Testing: Validates research hypotheses based on real-world data and outcomes.

Quick Start

Start a new session by loading the context and verify access to all repositories.

Frequently Asked Questions about lessons

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

FAQPage Schema
How do I analyze git history to identify AI-paired workflow patterns?▼

To analyze git history for AI-paired workflow patterns, this Skill examines your repository commits to identify trends, validate hypotheses, and generate actionable playbooks for project management and code review.

Can I use Octokit and Supabase to evaluate a portfolio of AI-paired projects?▼

Yes, you can evaluate a portfolio of AI-paired projects using Octokit and Supabase by analyzing repository health, identifying anti-patterns in git history, and validating workflow hypotheses against real-world data outcomes.

What is the best way to validate hypotheses about code review anti-patterns?▼

The best way to validate hypotheses about code review anti-patterns is to cross-reference git history data with project outcomes, ensuring insights pass a monetization gate for actionable value.

Do I need MCP tools and GitHub access to generate workflow playbooks?▼

Yes, you need MCP tools and GitHub repository access to generate workflow playbooks, as the analysis relies on examining git history and validating patterns directly from your AI-paired project data.

When should I not use AI-paired workflow analysis for project management?▼

You should not use AI-paired workflow analysis if your repositories lack sufficient git history depth or if you cannot provide GitHub access for the required MCP tools and Octokit integration.

How do I optimize my AI-paired workflow for solo builders and small teams?▼

You optimize AI-paired workflows by deep diving into git history to identify anti-patterns, testing research hypotheses, and applying generated monetizable playbooks to improve personal project management.

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