A Review Checklist for AI Replies With Setup Steps

When an AI-drafted support reply includes setup steps, check six things before you send it. Each one is a question:

1. Context: Do the steps match the customer's platform, version, and plan?
2. Accuracy: Does every step, button label, command, flag, and package name exist in your product today?
3. Order: Are prerequisites listed first, with one action per numbered step?
4. Safety: Could any step delete data, expose a secret, or ask for more permissions than needed?
5. Fit: Is this the shortest path for this customer, or a generic tutorial?
6. Finish line: Does the reply say how to confirm it worked, and what to send back if it didn't?

The rest of this post explains each check, how to run it quickly, and why setup instructions need more scrutiny than most support replies.

Why setup steps need a closer look

A wrong sentence in a support reply is usually just awkward. A wrong setup step makes the customer do something. They paste a command, change a config file, or install a package. If the step is wrong, the customer loses time at best. At worst, their environment ends up broken.

The documented risks are specific:

• Plausible but false output. The OWASP Top 10 for LLM Applications lists Misinformation (LLM09:2025) as a core risk. It describes hallucination as a model filling gaps with "statistically plausible" content, and it names overreliance as the factor that lets those errors through. One of its examples is Air Canada losing a case after its chatbot gave a traveler wrong information.
• Packages that don't exist. A study of 16 code-generating models, We Have a Package for You!, found 205,474 unique hallucinated package names across 576,000 generated code samples. The average hallucination rate was at least 5.2% for commercial models and 21.7% for open-source models. OWASP describes the matching attack: someone publishes a malicious package under a commonly hallucinated name and waits for people to install it.
• Human review is the recommended control. OWASP's mitigations for LLM09 include cross-verification, human review "particularly for critical or sensitive information," and training reviewers so they don't overrely on AI output themselves.

Setup instructions combine all three risks. They read as authoritative, they often contain commands and package names, and customers tend to follow them exactly.

The checklist in detail

1. Confirm the context before you read the steps

Before you check whether the steps are correct, check whether they are the right steps for this customer.

• [ ] Platform: Do the steps match the customer's OS, device, browser, or hosting environment? A macOS path sent to a Windows user is a common mismatch.
• [ ] Version: Do they match the version the customer is running? If the message doesn't say, ask, or write steps that hold across versions and say so.
• [ ] Plan or tier: Is the feature available on the customer's plan? Setup steps for a feature they can't access only add confusion.
• [ ] Starting point: Has the customer already tried some of these steps? Repeating what they said they did reads as if you didn't read their message.

If the original message is missing key details, a short clarifying question can be the right reply. These ways to ask for better bug reproduction steps apply to setup problems too.

2. Verify every step against the current product

This check catches the most errors and takes the most effort.

• [ ] UI labels: Do the menu names, buttons, and settings match what the customer will see today, including after your latest release?
• [ ] Commands: Does each command exist, and does it work with the flags shown? Check flags that look plausible but may not exist.
• [ ] Package and dependency names: Is each package name real, spelled exactly right, and the one you actually mean? Given the research above, look it up in the official registry instead of trusting that it sounds familiar.
• [ ] File paths and config keys: Are the paths, file names, environment variable names, and config keys spelled exactly as your product expects?
• [ ] Version numbers: If the reply pins a version, is it current and compatible?
• [ ] Placeholders: Are values the customer must replace clearly marked (for example YOUR_API_KEY) and explained?

For commands and code blocks, the guide on reviewing code snippets in AI support replies goes into more detail.

3. Check structure and order

Good procedures follow conventions that technical writers have refined over time. The Google developer documentation style guide on procedures is a useful reference. Several of its recommendations work well as review checks:

• [ ] Prerequisites first. The guide recommends telling readers what they need before they start: accounts, permissions, tools, versions.
• [ ] Numbered steps for sequences. A procedure is "a sequence of numbered steps." A single action doesn't need a numbered list.
• [ ] One action per step. The guide's general rule is "use one step for each action," and it warns against long steps.
• [ ] Imperative verbs. Each step should start with what to do: "Open," "Run," "Select."
• [ ] Location before action. For example: "In Settings > Integrations, select Add webhook."
• [ ] Action first, then result. Say what to do, then what the customer should see.
• [ ] Optional steps labeled. Start them with "Optional:" so nobody wonders whether a step is required.
• [ ] As few steps as possible. The guide advises documenting the best method rather than every possible method.

AI drafts tend to break the last rule. They often offer two or three alternative approaches "just in case." In a support reply, pick one approach and cut the rest.

4. Look for anything risky

Some steps deserve a pause even when they are technically correct.

• [ ] Destructive actions: Does any step delete, reset, overwrite, or migrate data? If so, does the reply say what will be lost and suggest a backup first?
• [ ] Secrets: Does the reply ask the customer to paste an API key, password, or token into the support thread? It shouldn't. Does it show a real-looking key where a placeholder belongs?
• [ ] Permissions: Does a step ask for admin rights, sudo, or broad access scopes the task doesn't need?
• [ ] Piped install scripts and third-party sources: Is the customer told to download or run something from a source you don't control? Is that source official?
• [ ] Instructions from the customer's message: Did text in the incoming message shape the steps in ways you wouldn't approve? The prompt injection checklist for AI support drafts covers this.

5. Make it fit this customer

• [ ] Right depth: A developer debugging an SDK and a non-technical user setting up an app integration need different levels of detail.
• [ ] No filler: Remove generic intros, background on how the feature works, and closing paragraphs that repeat the steps.
• [ ] Links are real and current: If the reply points to docs, each link should resolve to the right page and section. The link review checklist for AI support replies has a fuller process.
• [ ] Tone matches the situation: Someone blocked on setup for an hour wants a fast, clear path, not a cheerful preamble.

6. Define the finish line

Many setup replies stop at the last action. A better reply also tells the customer how to know they're done.

• [ ] Success check: What should the customer see when it works? A status message, a green indicator, specific command output?
• [ ] Failure path: If it doesn't work, what should they send back? Ask for the specific error message, log line, or screenshot that would help you, not "let me know if you have issues."
• [ ] Next step: If setup leads into another task, say so briefly or link to it.

How to run the checklist without it taking all day

Checking every step in full isn't practical for every ticket. A few habits help:

• Keep canonical setup steps. Write tested, current steps for your most common setup questions once. Reviewing a draft against a known-good version is much faster than checking it from memory.
• Test the unfamiliar parts. If a draft includes a command, flag, or package you don't recognize, check it before sending. Unfamiliarity is the signal.
• Re-check after releases. UI labels and CLI flags change. Treat setup replies as higher risk for a while after you ship changes to onboarding or configuration.
• Scale review to risk. A one-line "toggle this setting" reply needs a quick look. A ten-step migration with terminal commands needs the full checklist.

For general techniques on keeping reviews fast, see 5 ways to review AI replies without slowing down.

A hypothetical example

This exchange is illustrative, not a real customer case.

A customer writes: "I'm trying to connect your app to my Slack workspace but the integration isn't showing up."

An AI draft might reply with eight steps, including installing a CLI tool, setting an environment variable, and restarting a server. It covers both the hosted and self-hosted versions of the product.

Running the checklist on that draft:

• Context: The customer uses the hosted version, so the CLI and server-restart steps don't apply.
• Accuracy: The draft says "Settings > Apps," but the menu was renamed "Settings > Integrations" in a recent release.
• Fit: The real issue is probably plan-related. The integration might not be available on their tier.
• Finish line: The draft doesn't say what the customer should see once it's connected.

The revised reply could be three steps: confirm the plan, open Settings > Integrations, select Slack, plus one sentence on what a successful connection looks like and what to send if the option is still missing.

Where an AI drafting tool fits

The checklist assumes a human approves every reply, and that's the setup OWASP's guidance points toward for critical information. SupportMe is built around the same idea. It drafts replies in your writing style, but nothing sends without your approval. When you edit a draft, it compares its version with yours and uses the difference to update your style profile and knowledge base.

In practice, fixing a setup reply properly (correct labels, real commands, a clear success check) is part of how future drafts improve. Review is still your job, though, especially for setup steps.

If you want a lighter version of this list for daily use, this guide to building a support reply checklist in 10 minutes shows how to turn it into your own short template.

Conclusion

Customers follow setup steps exactly, so errors in them cost more than errors elsewhere in a reply. Before you send an AI-drafted reply with setup steps, check six things:

• the customer's context
• every label, command, and package name against the current product
• a clean structure with prerequisites first
• any risky actions
• fit for this customer
• a clear way to confirm success

Canonical steps and risk-based review keep this manageable, and they make each corrected reply a better reference for the next one.

References

• OWASP Gen AI Security Project, LLM09:2025 Misinformation
• Spracklen et al., We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs (USENIX Security 2025)
• Google, Developer Documentation Style Guide: Procedures