learn-from-repo

Extract evidence-backed architecture, testing, and security findings from GitHub, GitLab, or local repositories.

3|Updated Apr 5, 2026

Search Tags:#code-patterns #skill-discovery #repository-analysis #architecture-review #security-scan #credibility-assessment

One-click install

npx skills add https://github.com/dvy1987/agent-loom --skill learn-from-repo

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: learn-from-repo
Source: https://github.com/dvy1987/agent-loom/tree/main/.agents/skills/learn-from-repo
Command: npx skills add https://github.com/dvy1987/agent-loom --skill learn-from-repo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the difficult, time-consuming task of learning reusable engineering patterns, architecture decisions, code conventions, and security findings from a repository so teams can quickly decide what to adopt, adapt, or reject.

Core Features & Use Cases

Credibility assessment: Scores repos across reputation, maintenance, tests, docs, and adoption with a strict gate before extracting insights.
Security-first ingestion: Runs a full security scan pipeline and blocks ingestion on unsafe findings, including checks from secure-skill-repo-ingestion.
Code-backed extraction & recommendations: Scans source, tests, and CI to extract patterns and produces per-pattern recommendations (APPLY, PARTIAL, SKIP, KEEP CURRENT) with citations and an application plan.
Use Case: Evaluate an open-source project to mine testing strategies, dependency management patterns, and CI workflows for possible adoption into a skill library.

Quick Start

Analyze the repository at https://github.com/owner/repo and extract actionable architecture, code-convention, testing, and security findings with evidence-backed recommendations.

Frequently Asked Questions about learn-from-repo

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

FAQPage Schema

How do I extract actionable code patterns and architecture decisions from a GitHub repository?▼

Repository analysis scans the codebase to assess credibility, run security scans, and extract code-backed patterns. It scores reputation, maintenance, tests, docs, and adoption to ensure you only mine insights from trustworthy software repositories.

Can I run a security scan on a GitLab repository before adopting its code conventions?▼

Yes, you can run a full security scan pipeline on a GitLab repository to identify vulnerabilities before adopting its code conventions. The process blocks ingestion upon detecting unsafe findings, ensuring only secure patterns are extracted for your skill library.

What is the best way to evaluate an open-source project for testing strategies and CI workflows?▼

The best way to evaluate an open-source project is to perform a credibility assessment across maintenance, tests, and adoption, followed by extracting code-backed recommendations. This surfaces specific testing strategies and CI workflows with actionable guidance.

Does repository analysis work with local repository paths to assess credibility and find security findings?▼

Yes, repository analysis works with local repository paths to assess credibility and find security findings. It applies the same security scan pipeline and credibility gate to local directories to produce per-pattern recommendations and an application plan.

How do I get code-backed recommendations for dependency management patterns I want to adopt?▼

To get code-backed recommendations for dependency management patterns, scan the repository source and tests to extract evidence-backed citations. The analysis provides specific advice to APPLY, PARTIAL, SKIP, or KEEP CURRENT for each pattern.

When should I not use automated architecture review for mining engineering patterns?▼

You should not use automated architecture review when a repository fails the strict credibility gate or contains unsafe security findings. The process blocks ingestion on unsafe code, meaning low-reputation or unmaintained repos will not yield reliable engineering patterns.