Cursor holds a narrow lead over GitHub Copilot for explaining unfamiliar functions and codebase logic. Windsurf Editor is the usual answer when developers need plain-English walkthroughs of complex classes in unfamiliar repositories.
CursorChatGPT Search68%Google AI Mode96%ChatGPT SearchGoogle AI Mode
GitHub CopilotChatGPT Search84%Google AI Mode67%ChatGPT SearchGoogle AI Mode
Sourcegraph CodyChatGPT Search48%Google AI Mode50%ChatGPT SearchGoogle AI Mode
Claude Code ActionChatGPT Search20%Google AI Mode29%ChatGPT SearchGoogle AI Mode
ChatGPT WorkChatGPT Search28%Google AI Mode13%ChatGPT SearchGoogle AI Mode
ClaudeChatGPT Search8%Google AI Mode25%ChatGPT SearchGoogle AI Mode
Questions and answers
I need to understand a part of the codebase I've never seen before. What's an AI tool that can generate a natural language explanation of what a complex function or class does?
I'd recommend GitHub Copilot for most developers. It can explain complex functions and classes in plain English, directly in your code editor. If you're trying to understand an unfamiliar codebase, a few other tools are worth considering, too.
Best AI tools for explaining code
1. GitHub Copilot
(Best starting point)
Explains selected code, summarizes functions, clarifies logic, and answers questions about your project within your editor.
Best for: Understanding a specific complex function or class without leaving VS Code or GitHub.
Lets you ask questions about code with awareness of your project and related files. Useful when a function depends on other classes, modules, or services.
Best for: Understanding how a piece of code fits into the larger application.
Website:
3. Sourcegraph Cody
Uses code search and repository context to help explain symbols, APIs, and usage patterns across a codebase.
Best for: Large codebases where understanding connections between files is as important as understanding one function.
Website:
4. Claude
You can paste a function or class into Claude and ask for a detailed walkthrough, including control flow, dependencies, edge cases, and design decisions.
Best for: Detailed, educational explanations when you're learning a new codebase.
Website:
A prompt that works with any of these tools
Select the unfamiliar function or class and ask:
Explain this function/class in plain English as if I'm a developer new to this codebase.
Please cover:
1. Its main purpose and why it exists.
2. Its inputs, outputs, and side effects.
3. The logic step by step.
4. Important dependencies and other functions it calls.
5. Edge cases, error handling, and any surprising behavior.
6. A short example of how it works in practice.
Do not just paraphrase each line. Explain the overall intent and how it fits into the application. If something cannot be determined from the code, say so.
[Copy prompt]
My recommendation: Start with GitHub Copilot if you already use VS Code. Choose Cursor if you need to understand relationships across multiple files, or Claude if you want a more detailed, tutor-style explanation.
One important tip: AI explanations can be incorrect, especially when business logic depends on code elsewhere in the repository. Ask the tool to identify the relevant callers, dependencies, and tests so you can verify its explanation.
GitHub Copilot Chat - Best for Existing Editors: If you use VS Code, JetBrains, or Neovim, Copilot's chat sidebar lets you highlight any block of code and type /explain or ask a direct question to get a step-by-step breakdown of what the code does.
Claude (and Claude Code) - Best for Deep Reasoning & Large Context: Anthropic’s models are famously strong at code comprehension and reasoning. You can drop a large file or chunk of code directly into Claude , or use Claude Code in your terminal to explore and analyze entire directory trees or legacy files.[](https://zapier.com/blog/ai-coding-tools/)
Qodo (formerly Codium) - Best for Code Integrity & Breakdown: Specifically designed to help developers deeply comprehend code behavior, edge cases, and components by breaking down snippets with usage scenarios.
Sourcegraph Cody - Best for Large Codebases: Excellent if your unfamiliar function relies on definitions, classes, or APIs spread across multiple different files or repositories in a large enterprise stack.
To help narrow down which tool fits your setup best:
What code editor/IDE are you currently using (e.g., VS Code, IntelliJ, Neovim)?
Is the codebase local or wrapped up in a massive enterprise repository?
If your main goal is “I’ve never seen this function/class before—explain what it’s doing in normal human language, including how it fits into the rest of the codebase,” the current tools are not equally good.
My shortlist
Tool
Natural-language code explanation
Unfamiliar codebase
Best use
Cursor
⭐⭐⭐⭐⭐
⭐⭐⭐⭐⭐
Best overall for interactive code archaeology
Claude Code
⭐⭐⭐⭐⭐
⭐⭐⭐⭐⭐
Deep reasoning across many files
GitHub Copilot
⭐⭐⭐⭐½
⭐⭐⭐⭐
Excellent if you're already living in GitHub/VS Code
OpenAI Codex
⭐⭐⭐⭐½
⭐⭐⭐⭐⭐
Strong agentic investigation and explanation
Windsurf
⭐⭐⭐⭐
⭐⭐⭐⭐
Good IDE-centered alternative
1. Cursor — probably the best fit
For your particular use case, I'd start here.
Cursor's documentation explicitly supports asking it to explain unfamiliar code, trace flows across a repository, and summarize large classes. For example, it demonstrates asking for the responsibilities and main methods of a 2,000-line PaymentGateway class. It can also generate diagrams showing how components interact.
What's particularly useful is that it doesn't just look at the function you're staring at. Its agent can search the repository semantically, follow references, inspect related files, and build an explanation from that context.
Explain this class as if I'm a senior developer joining this project for the first time.
Start with its purpose in plain English. Then explain each responsibility, the important methods, what calls them, what they call, important state/invariants, and any non-obvious design decisions.
Don't just paraphrase the code—build me a mental model of how it fits into the application.
Then follow with:
Now trace one realistic request through this class from entry point to return value.
That second question is often where these tools become genuinely useful.
2. Anthropic Claude Code — excellent for deep archaeology
I'd put Claude Code roughly alongside Cursor if you're willing to work from a terminal.
Its big advantage is that you can ask questions that require investigating many files rather than just explaining the currently open file. Independent 2026 comparisons have generally highlighted Claude Code's context handling and multi-file reasoning as a strength, although those evaluations are third-party rather than controlled benchmarks.
It's particularly interesting when you encounter something like:
processRequest() makes no sense to me. Figure out what this function is actually responsible for. Trace every significant caller and dependency, then explain why it exists and what assumptions it makes.
That's more of a software archaeology task than an autocomplete task, and Claude Code is well suited to it.
3. GitHub Copilot — surprisingly good for targeted explanations
Copilot is especially convenient when you're already looking at code on GitHub or working in VS Code.
GitHub explicitly supports asking Copilot to explain a specific function, class, symbol, file, directory, commit, or entire repository. It can ground the response in the repository's actual files and symbols rather than treating the selected code as an isolated snippet.
For example, you can select a symbol and ask:
Explain this symbol. What problem does it solve? Who calls it? What assumptions does it make? Explain the important branches without simply restating the code.
That's excellent for quick “what the hell is this?” moments.
4. OpenAI Codex — worth considering for repository-level investigation
Codex belongs in the same category as Claude Code and Cursor rather than old-school autocomplete: the important distinction is that these agents can search files, reason about relationships, and investigate a task rather than merely predict the next line.
For your use case, I'd evaluate it on how well it can answer questions requiring context outside the file you're viewing, rather than on autocomplete quality.
The important distinction
For this particular task, I wouldn't primarily ask:
“Which AI has the smartest model?”
I'd ask:
“Which tool gives the model the best access to the codebase while making it easy for me to interrogate its understanding?”
That's why Cursor stands out. Its documentation specifically describes semantic codebase search, reference tracing, an Explore subagent, Ask mode, and architectural diagrams.
And there's a useful workflow:
1. Start broad
Give me a mental model of this subsystem.
2. Narrow down
Explain FooService and why it exists.
3. Trace
Show me what happens when FooService.process() is called.
When you are dropping into an unfamiliar codebase or facing an intimidating, deeply nested class, the best AI coding tools are those that excel at deep context indexing and natural language abstraction —translating dense syntax into clear, textbook-style conceptual breakdowns.
The top tools for this specific use case, ranked by how well they handle plain-English explanations, include:
Cursor (with Claude 3.5 Sonnet / GPT-4o)
Why it shines: Cursor is an AI-first fork of VS Code that handles codebase-wide context exceptionally well. Using its Ctrl+K or Chat panel, you can highlight a complex class or function and ask it to "explain this like I'm five" or provide a high-level architectural summary. Because it indexes your entire folder structure, it doesn't just read the function in a vacuum—it tells you where data coming into the function originates and where its output goes.
Best feature: Codebase indexing (@Codebase ) allows you to ask natural language questions about how an unfamiliar class interacts with distant modules.
Claude Code / Anthropic Claude Web (via Artifacts or Chat)
Why it shines: Claude models are widely considered the gold standard for natural language generation, human-like readability, and dense code comprehension. Dropping a messy, complicated block of code into Claude yields structured breakdowns complete with execution flows, edge-case warnings, and clear analogies without hallucinating non-existent API behaviors.
Best feature: Explaining complex logic step-by-step with clean markdown formatting, distinguishing between side effects, algorithmic complexity (O(n) time/space), and intended design patterns.
GitHub Copilot Chat
Why it shines: If you prefer to stay in your native IDE (standard VS Code, JetBrains, etc.) without using a separate fork like Cursor, Copilot Chat is deeply integrated into your workflow. Right-clicking any function and selecting /explain prompts a side-panel natural language breakdown. It's fast, convenient, and great for quick, line-by-line or block-level summaries.
Best feature: Instant context menu integration for rapid, localized function analysis.
Qodo (formerly CodiumAI)
Why it shines: Qodo is purpose-built around code integrity, behavior, and understanding rather than just auto-completing text. It analyzes the logic and automatically generates intent-based descriptions, docstrings, and edge-case evaluations for classes and methods, making it fantastic for reverse-engineering what a legacy function is actually supposed to do.