Before a coding agent edits files, ask it to check your request for ambiguity, assumptions, constraints, and risks—and to show you a plan first. This simple pause can expose misunderstandings while they are still cheap to fix. It is a workflow instruction, not a guarantee that the agent will catch every problem or produce better code.
What a pre-write audit asks the agent to do
The goal is to separate understanding the task from implementing it. Instead of letting the agent move directly from your request to file changes, ask it to explain what it thinks you want, identify decisions it cannot safely infer, and outline its proposed work.
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Try this prompt:
Before changing files, inspect my request. Restate the desired outcome, list unclear or conflicting requirements, identify assumptions and relevant constraints, and flag security or data-loss risks. Ask questions if a missing decision would change the implementation. Otherwise, show a concise plan and wait for my approval before editing.
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This is a practical prompt pattern, not an official vendor command. It works only to the extent that the agent notices and reports a problem. Read its restatement and plan carefully; if either conflicts with your intent, correct it before approving the work.
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How to use the pause in a coding workflow
- Give the agent the task and relevant context. Include the intended outcome, constraints, and any files or behavior that must not change.
- Request the audit before edits. Ask for unclear or conflicting requirements, assumptions, constraints, and security or data-loss risks.
- Resolve consequential questions. If a missing decision would change the implementation, answer it rather than letting the agent guess.
- Review the plan. Check that it covers the requested outcome and respects the constraints. Approve or revise it before file changes begin.
- Inspect the actual changes afterward. Compare the diff with the approved plan; approval of a plan does not establish that the implementation followed it.
Anthropic describes planning workflows, including plan mode, in its Claude Code developer use cases. OpenAI’s Codex CLI getting-started material describes an approval-oriented workflow where proposed patches and shell commands can be reviewed inline: OpenAI Codex CLI – Getting Started. These are related ways to introduce review; the documentation does not establish that every coding agent has the same feature or a dedicated prompt-audit command.
What the audit can—and cannot—catch
A written checklist can prompt the agent to surface an omitted requirement or an assumption before it acts. A built-in planning or approval flow can make that pause part of the product workflow. Neither should be confused with a technical permission boundary: asking an agent to wait does not, by itself, prevent it from accessing files or running commands.
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OpenAI recommends giving agents clear, specific instructions, limiting access to what they need, and reviewing consequential actions. Its prompt-injection guidance also warns that hidden content can try to steer an agent away from the user’s intent. Keep permissions narrow where possible and treat surprising instructions found in files or other content with care: Understanding prompt injections.
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A plan review is also not a code review. Changes can diverge from the plan, and a security check cannot establish that the result is correct for your application. Anthropic’s Claude Help Center says automated security reviews should complement, not replace, existing security practices and manual code reviews: Automated Security Reviews in Claude Code.
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| Approach | What it adds | What it does not establish |
|---|---|---|
| Prompt-only checklist | Asks the agent to inspect the task before implementation and present its interpretation. | It does not enforce a pause or block edits by itself. |
| Built-in planning or review mode | Can make plan review part of a product’s workflow. Claude Code documents plan-mode workflows; Codex CLI describes inline review of proposed patches and shell commands. | Those sources do not establish feature parity across products or that a plan guarantees the final changes will match it. |
| Permissions and security controls | Can constrain access or require approval for consequential actions, depending on the product and configuration. | They do not decide whether the task itself is well specified or whether the resulting code meets your requirements. |
For a small, reversible task, a short prompt and a quick diff review may be enough. For work that could delete data, change permissions, expose secrets, or alter production behavior, use a stronger approval boundary where available and inspect the resulting changes before accepting them. The right safeguard depends on the agent and its configuration; the cited product documentation describes related capabilities, not a universal setup.
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