Use a narrowly scoped question, give the assistant the exact code context it needs, demand file-and-symbol references, and enforce read-only permissions in the tool itself. A sentence such as “do not edit or run code” states your intent, but it cannot prevent changes or execution unless the selected mode and technical permissions also forbid those actions.
What a safe code-explanation session looks like
The safest workflow treats an AI explanation as a traceable hypothesis about the source, not as an authority. You identify one behavior, provide the relevant file or repository context, ask the assistant to follow the call path, and then open every cited location yourself.
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- Scope: one function, route, file, or request flow rather than an entire repository.
- Context: the selected lines, current file, directory, or permitted repository content that contains the implementation.
- Evidence: exact file paths, symbols, and line ranges where available.
- Boundaries: a question or read-only mode plus permissions that do not allow editing, dependency installation, service startup, or code execution.
- Verification: inspection of the cited source and focused follow-up questions for missing links.
This arrangement is useful whether you are onboarding to an inherited service, investigating a request path, or trying to understand a function before making your own change. It also keeps the explanation small enough to check.
Choose a behavior, not “the whole codebase”
Large, vague prompts invite a broad summary that may omit the branch you actually care about. Start with an observable behavior and a known entry point. Examples include:
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- “What does
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POST /ordersrequest reach the database write?” - “Explain this file’s role in the image-upload flow.”
- “Which functions transform the request body before it reaches the queue?”
Name the starting file, function, class, route, event handler, or command when you know it. If you do not know the entry point, ask the assistant to identify likely entry points in one directory first, then choose one for a second, narrower question. Asking for an explanation of an entire repository in one turn makes completeness difficult to judge.
Define the result you want
Decide whether you need a high-level overview, a call sequence, a data-flow explanation, or an explanation of one condition. A useful request states where the trace should end: a response, database operation, emitted event, rendered view, or returned value. This prevents the answer from wandering into unrelated modules.
Give the assistant the right code context
Open or select the relevant file and lines in the assistant’s supported interface. Some code assistants can use the current file or directory as context; repository-aware features may retrieve additional permitted files. The exact behavior depends on the product, IDE, account, and workspace configuration, so check what context was actually attached to the conversation.
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- Keep API keys, tokens, passwords, private certificates, customer data, and proprietary secrets out of prompts.
- Include imports, type definitions, interfaces, and error classes when they affect the path being explained.
- State the language, framework, runtime, and relevant version if the code’s behavior depends on them.
- Tell the assistant if a shown file is generated, vendored, or incomplete.
Use a prompt that produces a checkable explanation
Ask for an overview first, then a step-by-step trace. Require the assistant to separate what it can verify in the supplied source from assumptions it is making. Ask for open questions instead of allowing it to fill gaps silently.
Explain how [specific behavior] works in this repository.
Start at [entry point/file/function] and trace the relevant calls to [result].
Do not edit files, install dependencies, start services, or run project code.
Cite the exact files and symbols that support each step.
Separate verified facts from assumptions, and list open questions.
Keep the explanation focused on this behavior.The bracketed items are variables for your situation; replace them before sending the prompt. This wording is a practical template synthesized from official codebase-exploration guidance, not a guarantee that a particular assistant will obey every instruction.
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Request a trace rather than a paraphrase
A useful response should identify the entry point, show the order of calls, explain important branches and transformations, and state where the flow ends. Ask it to report the condition that selects each branch and the value passed between important functions. For asynchronous code, request the hand-off points: queue publication, callback registration, promise resolution, event emission, or worker consumption.
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Make uncertainty visible
Ask for three explicit categories:
- Verified: behavior directly supported by the supplied code and cited symbols.
- Assumed: an interpretation based on naming, conventions, missing files, or inferred runtime behavior.
- Open: a question that requires another file, configuration value, test, or human decision.
This prevents a plausible explanation from being mistaken for a complete one when the assistant lacked a dependency or could not observe runtime state.
Prevent changes with mode and permissions, not wording alone
Select an Ask, question, or read-only mode when the tool offers one. Then inspect the permission controls for the session or workspace. Disable file writes, shell execution, dependency installation, service startup, and other actions that are unnecessary for explanation. If your environment separates approval for reading, editing, and running commands, grant only the read access required for the selected files or repository.
“A prompt that says not to edit or run code is an instruction, not a permission boundary.”
This warning appears in Visual Studio Code documentation, “Explore a codebase with an agent.” It matters because an agent may have tools capable of changing files or running commands even when your prompt says not to. A read-only request is therefore a combination of intent, mode, and enforceable technical controls.
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- Confirm that the conversation is in a question or read-only mode, if available.
- Review the attached files, directory scope, and repository connection.
- Check whether the agent can write files, run a terminal, install packages, start processes, or invoke external services.
- Remove or redact secrets and personal data from the visible context.
- Send the narrow explanation request and watch for any proposed action or tool call.
Mode names and controls differ across IDEs and assistants. Do not infer a security property from a label alone; read the current documentation for the exact environment and verify the effective permissions.
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How common code-explanation surfaces differ
The same question can behave differently depending on where you ask it. Compare the environment on the dimensions that affect a no-change explanation.
| Surface | Relevant capability | What to verify before use |
|---|---|---|
| GitHub Copilot Chat | The /explain slash command asks about code in the currently displayed file. Ask mode is described as being optimized for codebase questions. |
Whether the current file, directory, or repository context is attached; which editing or agent modes are enabled in your IDE; and what actions those modes can perform. |
| Visual Studio Code codebase agent | Guidance covers repository questions, file and symbol references, and checking an explanation against the source. | Whether the selected agent has write or execution tools, and whether your workspace policy allows the requested repository access. |
| Codex CLI | The documented agent can read, modify, and run code locally, so it can support code understanding but is not inherently read-only. | Current commands, approval settings, filesystem permissions, and whether shell execution is disabled for the session. The relevant Help Center guidance is older than the other documentation, so confirm current behavior. |
| ChatGPT GitHub connection | The GitHub app is characterized as read-only analysis and search for repository content the user has permitted. | Whether the feature is available in your ChatGPT experience, which repositories and branches your account can access, and the workspace’s repository policy. |
| Another repository-aware assistant | Capabilities are not uniform; some can answer questions while others can also edit or execute. | Context access, a question or read-only mode, action permissions, file/symbol linking, and account authorization for the repository. |
These are capability categories, not a ranking. A tool is suitable only when it can see the code needed for the question and its effective permissions match your no-change requirement.
Verify the explanation against the source
Do not accept a confident narrative without checking its references. Open each cited file and symbol and follow the path in the stated order. Confirm that names, conditions, return values, and error paths match the implementation.
- Check the entry point. Make sure the assistant started at the function, route, event handler, or command you intended.
- Follow each call. Open the referenced definition, not merely a similarly named helper or test double.
- Inspect branch conditions. Verify the predicates, default values, feature flags, and exception handling that select the path.
- Track data changes. Compare input and output types, serialization, validation, mutation, and mapping between layers.
- Check the endpoint. Confirm the final response, write, event, or returned value the explanation claims.
- Record gaps. If a cited file is missing from context or a runtime value is unknown, mark the conclusion as unverified.
If the answer skips a link, ask a follow-up about that exact transition: “How does createOrder reach persistOrder? Cite both definitions and the call site.” Narrow follow-ups are easier to validate than asking the assistant to rewrite its entire answer.
Repository questions that work well
For a directory you do not know, begin with a map rather than an exhaustive explanation:
Explain the files in this directory. For each file, state its purpose,
important public symbols, and references to other files. Do not edit or run
anything. Cite the paths used, and mark any purpose you inferred.After reviewing the map, choose the file that contains the behavior you need. You can then ask for a focused trace:
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Trace the request from the handler in src/routes/orders.ts to the response.
List each function and file in order, the data passed between them, and every
error branch. Cite symbols. Do not edit files, install dependencies, start
services, or run project code. Separate verified facts from assumptions.For a single function, reduce the scope further:
What does parsePermissions do for an empty claim and for an unknown claim?
Use only the selected file and its referenced type definitions. Cite the
conditions and return values. Do not change or execute code.Common failure modes and fixes
The answer summarizes names but not behavior
Symptom: You receive descriptions such as “this service handles orders” without a call sequence or conditions.
Fix: Specify an entry point and endpoint, then require each function, file, branch, and data transformation in order.
The assistant cites files you did not provide
Symptom: The response refers to a module, configuration, or test that was not in context.
Fix: Ask whether it actually accessed that file. Attach the file through the supported repository context or treat the claim as unverified. Never assume a familiar path exists because the name sounds plausible.
A similar symbol is mistaken for the real one
Symptom: The explanation follows a mock, overload, generated file, or deprecated implementation.
Fix: Request the exact definition and call site, including the module path and namespace. Check imports and the build configuration yourself.
Runtime behavior is presented as source certainty
Symptom: The assistant claims a network response, environment variable, feature flag, or database state that cannot be established from the files shown.
Fix: Ask it to label the statement as an assumption and list the configuration or runtime evidence required to verify it. Do not run the project merely to satisfy an explanation prompt if your session is intended to remain read-only.
The tool proposes an edit or command
Symptom: It offers to “fix,” refactor, install a package, run tests, or start a service while explaining the code.
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Fix: Decline the action, end the session if permissions are unclear, and re-open the question in a mode with those capabilities disabled. A repeated promise not to change anything is not a substitute for restricted permissions.
The explanation is too broad to audit
Symptom: Hundreds of lines cover unrelated modules and you cannot tell which claims answer your question.
Fix: Split the task by behavior or hop in the call chain. Ask one question about the entry point, another about the persistence or response step, and a final question about the error path.
Limits you should plan for
AI tools can omit a dependency, misunderstand a dynamic dispatch, miss generated code, or infer behavior from naming conventions. Repository indexing may be incomplete, and account or workspace policy can restrict which files are visible. Interfaces and permission controls also change over time. These limits mean that an explanation is a starting point for inspection, not a replacement for reading the implementation or consulting project documentation.
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There is no established numeric claim here about explanation accuracy, speed, or learning impact. The useful guarantee is procedural: a narrow question, visible evidence, constrained permissions, and source verification give you a way to detect and correct an incomplete answer.
A repeatable no-change checklist
- Choose one behavior and identify its entry point and endpoint.
- Select only the files, lines, directory, or permitted repository context needed to trace it.
- Redact secrets and state language, framework, runtime, and version details that affect interpretation.
- Use a prompt that requests a call sequence, file-and-symbol citations, verified facts, assumptions, and open questions.
- Use Ask or read-only mode when available.
- Disable or reject writing, shell execution, dependency installation, service startup, and external actions.
- Inspect every cited location and confirm branches, data transformations, and the final result.
- Ask focused follow-ups for missing links instead of requesting a broader summary.
- Record unresolved questions for a human review, test, or later investigation conducted under an appropriate permission set.
Following these steps lets an AI assistant explain unfamiliar code while keeping the actual repository unchanged and the reasoning traceable to source.
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