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Add-on module. Review Steps is a module that is not enabled by default. Contact your Cernel representative to enable it for your organization.
Review steps are checks you add to an AI agent. Each one reads a prompt you write and inspects every enrichment the agent produces, then decides what should happen when an enrichment fails: let it through, hold it for a person to approve, or reject it outright. They are how you enforce the standards that matter for your catalog, compliance and regulated claims, brand governance, factual accuracy, and tone of voice, so you can run enrichment at scale and still trust every value that goes live.

How it works

A review step is a prompt-based check that lives on an agent. When the agent enriches a product, each of its review steps looks at the value the agent just wrote and judges it against your instruction, for example “Fail the enrichment if it claims the product is sustainable, recycled or eco-friendly without the product data saying so.” The step returns a simple verdict: Passed or Failed. What happens on a failure is your choice, set per step under If this check fails:
  • Ignore it reaches your catalog as usual. The failed check is still recorded, so you can look at it later.
  • Hold for review makes the enrichment wait for a person to approve or reject it before it reaches your catalog.
  • Reject rejects the enrichment outright, so it never reaches your catalog.
The value the agent generated is always written down either way. A review step decides whether that value is allowed to go live, not whether it exists, so a held or rejected value is still visible to you in Review with its full history.

Why you would use this

Meet compliance rules

Stop regulated or unsupported claims, health, safety, sustainability, before they reach a storefront or a marketplace feed, where a wrong claim can mean a takedown or a fine.

Enforce brand governance and tone of voice

Hold every value to your content rules and brand voice: no competitor names, no banned superlatives, the register and reading level your brand uses.

Validate claims against the facts

Catch materials, specifications or certifications a value asserts that your product data does not actually support, so the AI cannot talk your catalog into claims you can’t stand behind.

Govern enrichment at scale

Apply the same standard to thousands of values automatically, holding back only the ones that need a human eye, so quality control keeps pace with the AI.

What to check for

A review step is just a prompt, so it can enforce almost any standard you can describe in a sentence. The most common uses:
  • Compliance and regulated claims. “Fail the enrichment if it makes a medical or health claim, such as cures, treats or prevents, that the product data does not support.”
  • Brand governance and safety. “Fail if the text names a competitor brand, or uses absolute superlatives like ‘best’ or ‘number one’ without evidence.”
  • Claim validation and accuracy. “Fail if it states a material, dimension or certification that is not present in the product data.” (This is the built-in example: “Fail the enrichment if it claims the product is sustainable, recycled or eco-friendly without the product data saying so.”)
  • Tone of voice. “Fail if the tone is casual or uses slang. Our brand voice is warm but professional, and we address the reader in the second person.”
  • Formatting and length. “Fail if the meta description is longer than 160 characters, or if it contains HTML tags.”
  • Language and market. “Fail if the text is not written entirely in French.”
Key concept: the strongest consequence wins. An agent can have several review steps, and a single enrichment can fail more than one. When it does, the strongest consequence among the failed steps applies: one step set to Reject is not softened by another set to Ignore it. So a value is rejected if any failed step rejects, held if any failed step holds and none reject, and let through only when every failed step is set to ignore. This lets you mix a hard compliance gate (Reject) with a softer brand-voice check (Hold for review) on the same agent.

Step-by-step guide

1

Open the Review Steps tab on an agent

Create or edit an agent in the Agent Sandbox. In the configuration panel on the left, open the Review Steps tab. The tab shows how many checks the agent has, and you can add up to 3 review steps per agent.
The Review Steps tab on an agent, showing an empty state that reads 'Check enrichments before they reach your catalog' with an Add review step button
2

Add a review step and write its prompt

Click Add review step. Give the step a Name, then write the Review step prompt that describes what an enrichment must do to pass. Be concrete and phrase it as a failing condition, for example “Fail the enrichment if it …”.
Keep each step focused on one thing. A prompt that checks a single, clearly stated rule is easier for the reviewer to apply consistently than one that bundles several rules together. Add a second or third step for the other rules.
3

Choose what happens when the check fails

Under If this check fails, pick the consequence: Ignore it, Hold for review, or Reject. The step summary reflects your choice, for example Held for review when it fails or Rejected when it fails.
A configured review step with a name, a prompt describing a failing condition, and the If this check fails options showing Ignore it, Hold for review, and Reject
4

Save the agent and run enrichment

Save the agent. From now on, every enrichment this agent writes is checked by its review steps. Run enrichment as usual, then open Review to see the results.
The agent now carries its review steps. When you run enrichment, values that fail a check are held or rejected according to the consequence you set, and you will see the outcome in Review.
5

See the verdicts in Review

On the Review surface, each proposed value shows whether it passed or failed its checks. A value card carries a shield: green when every step passed, and marked as failed when any step did not. Open it to see the per-step verdicts, each labelled Passed or Failed, with a summary such as 2 of 3 review steps failed or The enrichment passed all 3 review steps, and a note explaining the consequence that was applied.
Values that were rejected by a review step are hidden from the queue by default. Turn on Show failed, skipped & rejected in the Review toolbar to see them. A rejected value never reaches your catalog, so once you have looked at it you can Dismiss it to clear it from the queue.
A review step decides whether a value can go live, not whether the agent runs. If the review steps themselves could not run for an enrichment, Cernel lets the value through and flags it, with a note that reads The review steps could not run, so you know to give it a closer look than usual.

Advanced configuration

Every review-step verdict can show its reasoning. On a value, open How the reviewer reached this to read why the check passed or failed. Where the reasoning was not captured inline, a Why did the review steps say this? button generates the explanation on demand, so you can always see the thinking behind a verdict.Use this when a verdict surprises you: the reasoning usually shows whether the check read the value the way you intended, which tells you whether to reword the value or the review-step prompt.
Keep each check about one clear standard, and phrase it as the failing condition, “Fail the enrichment if …”, so the verdict is unambiguous. Judge the value on what it says or shows, its wording, claims, tone, or format, rather than on how it was generated. A claim-validation check can hold the value against the product’s own data, as the built-in example does when it fails a sustainability claim the product data does not support. If a verdict comes back wrong, open its reasoning to see how the check read the value, then tighten either the value’s prompt or the review-step prompt.
Review steps work alongside your organization’s approve-before-push setting. A value that every check passes still follows your normal Review setting for that run. A value a check sets to Hold for review is always collected in Review for a person to decide, even on a run where approval was otherwise off. This lets you keep most enrichment flowing automatically while still stopping the specific cases your checks catch.

Frequently asked questions

Up to three. The tab shows a of used count so you can see how many you have added. If you need more distinct checks than that, focus each step on the rule that matters most, since a single well-aimed check is more reliable than several loosely combined ones.
No. The value the agent generated is always written down and kept, with its full history. A review step only decides whether that value is allowed to go live: Ignore it lets it through, Hold for review waits for a person, and Reject stops it from reaching your catalog. A held or rejected value stays visible to you in Review.
The strongest consequence wins. If any failed step is set to Reject, the value is rejected. If none reject but any failed step is set to Hold for review, the value is held. The value is only let through when every failed step is set to Ignore it.
They are hidden from the Review queue by default because there is nothing to approve. Turn on Show failed, skipped & rejected in the toolbar to see them, read the reasoning, and Dismiss each one once you have looked at it.
That means the review steps could not run for that enrichment. Rather than block your catalog, Cernel writes the value and flags it with The review steps could not run. Give those values a closer look, and if it keeps happening, re-run enrichment on the affected products.

What’s next

Agent Sandbox

Build and refine the agent your review steps run on, and test it on real products first.

Jobs and Review

See how proposed values move through Review, where your review-step verdicts appear.

Completeness Score

Track how much of each category’s data is filled in once your agents and checks are in place.

AI Agents

Learn the full agent setup: prompts, Data Sources, dependencies, and linking agents to categories.