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Code Explanation Prompt (ChatGPT)

Code explanations are most valuable during onboarding, code review, and incident analysis. This prompt produces a layered explanation (summary → walkthrough → concepts → gotchas) that serves readers at different levels of depth. The concrete example walkthrough is what makes complex algorithms click. This variant is formatted for ChatGPT: Optimised for GPT-4o and GPT-4 Turbo. Uses markdown formatting and system/user message separation.

Prompt Template
## System
You are an expert AI assistant. Respond using clear markdown formatting.

## User
You are an expert software engineer and technical educator.

Explain the following {{language}} code to someone with {{audience_level}} knowledge.

Code to explain:
```{{language}}
{{code}}
```

Context: {{context}}

Provide:
1. **One-sentence summary** — what this code does at the highest level
2. **Step-by-step walkthrough** — explain each significant section in plain English
3. **Key concepts** — explain any non-obvious patterns, algorithms, or language features used
4. **Data flow** — describe how data enters, is transformed, and exits
5. **Gotchas** — any subtle behaviours, edge cases, or side effects a reader might miss
6. **Example** — walk through one concrete example input and show the output at each step

Variables

{{language}}Programming language of the code
{{audience_level}}Reader expertise, e.g., "junior developer", "non-technical stakeholder", "experienced developer unfamiliar with this pattern"
{{code}}The code to explain
{{context}}Where this code is used, e.g., "authentication middleware", "data pipeline step", or "unknown"

Example

Input
language: JavaScript
audience_level: junior developer
context: utility function used across the codebase
code:
const memoize = (fn) => {
  const cache = new Map();
  return (...args) => {
    const key = JSON.stringify(args);
    if (cache.has(key)) return cache.get(key);
    const result = fn(...args);
    cache.set(key, result);
    return result;
  };
};
Output
**Summary:** Creates a cached version of any function that remembers previous results to avoid redundant computation.

**Walkthrough:**
1. Takes a function `fn` as input
2. Creates a Map to store previous results
3. Returns a new function that: checks the cache first, computes if not cached, stores and returns the result

**Key concepts:** Closure (the inner function remembers `cache`), higher-order functions, memoisation pattern

**Gotcha:** JSON.stringify fails for circular objects and treats functions as undefined — not suitable for those input types.

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FAQ

Can this explain minified or obfuscated code?
Partially. The AI can usually explain the structure and patterns, but variable name mangling in minified code reduces accuracy. For obfuscated code, ask for a best-effort explanation and verify against the original source if available.
How do I explain code that spans multiple files?
Include the main file plus key imports and type definitions. Describe what each included file does in the context field. The AI will integrate the context to explain how the pieces interact.
Can I use this to explain shell scripts or SQL queries?
Yes. Set language to "bash" or "SQL" and it works equally well. For shell scripts, the step-by-step walkthrough is particularly valuable since bash syntax is notoriously cryptic.

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