code-explanation
Get layered, context-aware explanations of unfamiliar code. Understand what it does, why it was written that way, and how to work with it safely.
适合你,如果经常需要快速理解不熟悉的代码片段或遗留系统
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
~/.claude/skills/(项目级 .claude/skills/)~/.codex/skills/npx oh-my-skill add developersglobal/ai-agent-skills/code-explanationcurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- developersglobal/ai-agent-skills/code-explanationnpx oh-my-skill verify developersglobal/ai-agent-skills/code-explanation怎么用
技能原文 SKILL.md
Overview
Understanding unfamiliar code is a daily engineering task — onboarding to a codebase, debugging a library, or reviewing a PR. AI agents can explain code, but without structure, explanations are either too high-level to be useful or too detailed to absorb.
This skill produces layered, targeted explanations: start with what it does, then why, then how to work with it.
When to Use
- Onboarding to an unfamiliar codebase
- Understanding a complex function or algorithm before modifying it
- Debugging code you didn't write
- Reviewing a PR for a part of the system you don't know well
Process
Step 1: The 30-Second Summary
- In 2–3 sentences: What does this code do? What problem does it solve?
- What is the expected input? What is the output/effect?
- Where does this fit in the larger system?
Deliver: A 2–3 sentence plain-English summary a junior engineer can understand.
Step 2: Key Concepts and Patterns
- What design patterns does this use? (observer, factory, pipeline, etc.)
- What external libraries or frameworks are being used and why?
- Are there any non-obvious algorithmic choices? (Why O(n log n) and not O(n²)?)
- What are the key data structures and why were they chosen?
Deliver: 3–5 bullet points explaining the key design decisions.
Step 3: Execution Walkthrough
- Walk through the primary execution path step by step.
- For each significant step: what happens? what state changes?
- Highlight any surprising or non-obvious behavior.
- Show example input → output.
Deliver: A numbered step-by-step walkthrough of the happy path.
Step 4: Edge Cases and Gotchas
- What inputs cause unexpected behavior?
- What are the performance characteristics? (O(n) per call? Expensive on large inputs?)
- What side effects does this have? (Modifies global state? Makes network calls?)
- What could go wrong? What does failure look like?
Deliver: A "watch out for" section with at least 2 gotchas.
Step 5: How to Work With This Code Safely
- What should you not change without fully understanding? (Invariants, contracts)
- What tests cover this code? Are there gaps?
- What would break if you changed X?
Deliver: Specific guidance for safely modifying or extending this code.
Common Rationalizations (and Rebuttals)
| Excuse | Rebuttal | |--------|----------| | "I'll just read it" | Reading unfamiliar code without structure is slow and error-prone. Use the layered approach. | | "I'll ask a colleague" | Colleagues are often unavailable. AI can give a first-pass explanation 24/7. | | "I understand it well enough" | "Well enough" has caused many production incidents. Confirm your understanding. |
Red Flags
- Making changes to code you don't understand
- Assuming behavior without verifying it
- Skipping the "gotchas" section when under time pressure
Verification
- [ ] 30-second summary written (would pass the "elevator test")
- [ ] Key design decisions explained
- [ ] Happy path walkthrough complete with example
- [ ] At least 2 gotchas identified
- [ ] Guidance on safe modification provided
References
- [surgical-changes skill](../surgical-changes/SKILL.md)
- [debugging-methodology skill](../debugging-methodology/SKILL.md)