Verified:GitHub

maestro-learn

Guide structured codebase learning through evidence gathering and pattern extraction.

76|5|Updated Jul 7, 2026

Search Tags:#code analysis #investigation #learning #pattern extraction #engineering workflow #second opinion #guided reading

Ready to run

npx skills add https://github.com/catlog22/pi-maestro-flow --skill maestro-learn

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: maestro-learn
Source: https://github.com/catlog22/pi-maestro-flow/tree/main/.pi/skills/maestro-learn
Command: npx skills add https://github.com/catlog22/pi-maestro-flow --skill maestro-learn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users build a reliable understanding of code, decisions, and plans when simple reading is not enough. It is designed for guided learning, investigation, pattern extraction, and getting a second opinion on technical work.

Core Features & Use Cases

Guided reading: Walk through a code path section by section with forcing questions to build an understanding map.
Hypothesis-driven investigation: Answer a specific question by collecting evidence, forming hypotheses, testing them, and writing a report.
Pattern decomposition: Extract reusable design, behavioral, data, and error-handling patterns from a module or directory.
Second-opinion analysis: Review, challenge, or consult on code and plans from multiple perspectives.

Quick Start

Use the maestro-learn skill to investigate the target code path and summarize the key patterns, assumptions, and risks.

Frequently Asked Questions about maestro-learn

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

FAQPage Schema

How do I learn and understand a complex codebase instead of just reading it ad hoc?▼

Guided codebase learning uses structured reading, evidence gathering, and pattern extraction to build reliable understanding. It walks through code paths section by section with forcing questions to create an understanding map.

What is hypothesis-driven code investigation and how does it work?▼

Hypothesis-driven code investigation answers specific technical questions by collecting evidence, forming hypotheses, testing them, and writing a report. This ensures grounded understanding rather than superficial inspection.

How can I extract reusable patterns from a module or directory?▼

Pattern decomposition extracts reusable design, behavioral, data, and error-handling patterns from a module or directory. It anchors findings and cross-references conventions to persist learning artifacts for repeatable analysis.

Can I get a second opinion on technical decisions and code plans?▼

Second-opinion analysis reviews, challenges, and consults on code and plans from multiple perspectives. It applies to targeted engineering questions requiring grounded understanding and evidence-backed workflows.

What is the best way to investigate a code path and summarize its risks?▼

Investigate the target code path through guided reading and evidence gathering to summarize key patterns, assumptions, and risks. This requires anchored findings and convention cross-references for reliable analysis.

When do I need guided reading for an engineering workflow?▼

Guided reading is needed when simple code reading is insufficient to build reliable understanding. It applies to code paths, modules, wiki entries, and technical decisions requiring evidence-backed, persisted learning artifacts.