luongnv89/claude-howto
Agent skills in the GitHub repository luongnv89/claude-howto, each with its code score out of 100.
A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
- Repository score
- 58 / 100 C
- Skills
- 14
- Verified
- 3
- Average skill score
- 54
- GitHub stars
- 47,000
- License
- MIT
Open luongnv89/claude-howto on GitHub
14 skills in this repository
-
self-assessment
Comprehensive Claude Code self-assessment and learning path advisor. Runs a multi-category quiz covering 10 feature areas, produces a detailed skill profile with per-topic scores,…
Verified90A -
lesson-quiz
Test a learner on a single Claude Code tutorial lesson (01-10) with 10 questions, scoring answers and flagging weak spots. Use before, during, or after a lesson. Don't use for who…
Verified84B -
refactor
Systematic code refactoring based on Martin Fowler's methodology. Use when users ask to refactor code, improve code structure, reduce technical debt, clean up legacy code, elimina…
Verified82B -
claude-md
Create or update CLAUDE.md files following best practices for optimal AI agent onboarding
76B -
blog-draft
Draft a blog post from ideas and resources. Use when users want to write a blog post, create content from research, or draft articles. Guides through research, brainstorming, outl…
61C -
code-review-specialist
Comprehensive code review with security, performance, and quality analysis. Use when users ask to review code, analyze code quality, evaluate pull requests, or mention code review…
61C -
doc-generator
Generate comprehensive, accurate API documentation from source code. Use when creating or updating API documentation, generating OpenAPI specs, or when users mention API docs, end…
52D -
brand-voice
Ensure all communication matches brand voice and tone guidelines. Use when creating marketing copy, customer communications, public-facing content, or when users mention brand voi…
51D -
43D
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40D
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34F
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31F
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29F
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27F
Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.