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How to Use an AI Coding Agent to Diagnose Bugs Without Letting It Change Code

A “don’t edit” prompt is not a safeguard. Restrict the agent’s tools, check terminal and network boundaries, and verify its evidence before separately approving any code change.
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You can use an AI coding agent to investigate a bug without authorizing code changes—but a “don’t edit” prompt is not a technical safeguard. Restrict the tools the agent can use, check how its terminal and external access are controlled, and ask it to support its diagnosis with verifiable evidence. Treat any later fix as a separate task that requires your approval.

What “read-only” needs to mean

An agent session may have several ways to affect your project. Check three separate controls before sharing a repository:

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  • Tool availability: Can the agent only read and search files, or can it also edit files, run a terminal, use MCP servers, search the web, or contact other services? Removing write tools is stronger than leaving them available and asking the agent not to use them.
  • Approval or permission settings: Does the host ask before certain actions, or allow them automatically? An approval prompt can help you supervise actions, but it is not the same as making an action impossible.
  • Sandbox boundaries: Are commands limited by operating-system restrictions on filesystem or network access? Find out which tools the boundary covers. A terminal sandbox may not constrain an agent’s built-in file tools.

These controls work differently and are product-specific. Configure the active session, then verify its effective settings; do not assume a prompt or a default mode provides a hard boundary.

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Prepare a useful, low-risk bug report

Give the agent enough context to investigate, while avoiding unnecessary access or sensitive data. Include:

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  • The exact behavior you observed and the expected behavior.
  • Minimal reproduction steps, including relevant inputs and environment details.
  • Relevant error messages or logs, with credentials, tokens, personal data, and other secrets removed.
  • The likely entry point or affected area, if you know it.

Ask it to inspect only what is needed. Commands that appear diagnostic may still create caches, update snapshots, run migrations, mutate a database, contact a service, or change repository state. If a check might have side effects, have the agent explain what it would do before you authorize it.

Use a prompt that demands evidence

This template sets expectations and asks for a useful diagnosis. It communicates intent; it does not technically prevent an otherwise permitted action.

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Diagnose this bug using read-only inspection only. Do not edit, create, delete, or reformat files. Do not run commands that write files, change repository state, contact external services, or alter infrastructure. First restate the observed behavior and reproduction steps. Then identify the likely cause and cite the files, symbols, and lines that support it. Separate confirmed observations from hypotheses, list alternative explanations, and suggest read-only checks that would distinguish them. If a requested check requires a write, a command with side effects, or network access, stop and explain what it would do instead of running it.

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Paths, symbols, and line references make the explanation easier to verify, but do not make it proof. Ask the agent to distinguish what it directly observed from what it inferred, and to name alternative explanations rather than present its first hypothesis as certain.

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Choose controls for the coding agent you use

Product labels and capabilities can change. Check the documentation for the version and host you are using, then confirm the active session’s settings.

OpenAI Codex

The Codex CLI documentation describes Codex as able to inspect files, edit them, and run local tools. It directs users to /permissions to set boundaries for file edits and command execution. Codex also documents a review workflow that reports prioritized findings without modifying the working tree, and recommends Git checkpoints before and after a task. Use the current product’s permission labels and verify the mode in your installed version rather than relying on remembered names.

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Visual Studio Code agent sessions

Microsoft’s trust and safety documentation describes agents that can read and edit files, run commands, and call external services. It recommends reviewing generated code before committing and warns that restoring workspace files does not reverse completed terminal commands, network requests, deployments, or changes to external services.

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VS Code’s approvals documentation says common read-only terminal commands run automatically by default, while risky commands such as rm and del require approval. It calls terminal auto-approval a best-effort convenience, not a security boundary, and notes that complex syntax or obfuscation can evade command detection. The documentation also describes terminal sandboxing as Preview on macOS, Linux, and WSL2 and Experimental on Windows at the time reviewed; these release states can change.

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Crucially, VS Code says terminal sandboxing applies to shell subprocesses, not built-in file tools. File read, edit, and write tools use VS Code’s permission system, so terminal sandboxing alone does not prevent every agent file edit.

Claude Code

Anthropic’s Claude Code power-user documentation gives an example of a custom ReadOnly agent restricted to the Read tool, without edit or bash capability. That illustrates a stronger approach than relying only on instructions in a prompt: remove capabilities the diagnostic session does not need. Check Anthropic’s current documentation for the configuration syntax you use.

Gemini Code Assist

Google Cloud’s agent-mode documentation says filesystem-modifying and other mutating tool requests require user permission unless those tools are configured to always be allowed; read-only requests might not require permission. Depending on IDE and configuration, agent mode can use tools such as grep, file read and write, Google Search, MCP servers, and a terminal. A request that might not trigger an approval prompt is not necessarily a request the agent cannot make.

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Constrain terminal, network, and external-service access separately

If the agent has a terminal, decide whether it needs one for diagnosis at all. Removing terminal access can avoid command side effects. If commands are necessary, limit them to the checks you understand and authorize, and use the host’s sandbox where available. Verify whether that sandbox restricts filesystem and network access, and which agent tools it covers; do not assume a shell restriction also applies to built-in file tools.

Consider external access separately. Search, MCP servers, and other integrations can reach beyond the local codebase, and may have their own trust or approval controls. For a diagnosis that only needs repository inspection, disable or restrict capabilities that are not needed. If a proposed check requires network access or could affect an external service, have the agent stop and explain it before proceeding.

Verify the diagnosis, then decide whether to authorize a fix

  1. Check the effective session configuration. Confirm that write tools are absent or appropriately restricted, and determine whether terminal, network, and integrations are available. Do not infer a restriction from the prompt text alone.
  2. Record repository state when appropriate. Check git status or an equivalent before and after the investigation. This can reveal workspace changes, but it cannot show every external side effect or undo a completed command, request, or deployment.
  3. Validate the evidence. Open the cited files and confirm the relevant symbols, lines, and behavior. Follow the reproduction steps yourself and use the suggested read-only checks to distinguish the agent’s hypothesis from alternatives.
  4. Make implementation a separate decision. If you want a fix, explicitly authorize that new task. Review the proposed diff before commit, merge, or pull request; do not treat the diagnostic request as permission to implement.

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