Checklist or SOP

TL;DR
To write a Sponsored Ads SOP a new hire can follow, break your weekly routine into steps that each name the data to pull, the rule to apply and the person who confirms the change. Then hand the same steps to Xnurta MCP as a skill by describing the scenario, the rules and the output you want back. This guide is for Amazon ad managers who run search term reviews every week and are tired of walking each new person through them.
It names the data, the rule and the person who confirms, on every step. "Review search terms weekly" is a reminder. "Pull 30 days of search terms, flag any that spent more than [X] with zero orders, get a senior to approve the negatives" is an SOP. New hires rarely trip on judgment first. They trip on gaps: which window, which threshold, who says yes.
Most teams keep that routine in one person's head and a half-finished doc. The same document can become your team's first skill. Xnurta MCP connects Claude, ChatGPT and other MCP clients to your Xnurta data, and a skill teaches the assistant a routine on top of that connection. If you have not connected yet, start with Connect Claude or ChatGPT to Xnurta MCP.
Seven steps, and five of them only read. The template below covers a Monday search term review for one ad account. Swap every bracket for your team's own number, because the thresholds are yours, not ours.
| Step | You do | The assistant does | Who confirms |
|---|---|---|---|
| 1. Check recent changes | Name the ad account and ask for the last [14] days of actions. | Reads the operation log for human and AI actions. | No one. Read only. |
| 2. Pull search terms | Set the window, for example the last [30] days. | Lists search terms with CTR, CVR, ACOS and orders. | No one. Read only. |
| 3. Flag negatives | Set the rule: spent more than [X] with no orders, not yet negated. | Lists every term that matches. | No one. Read only. |
| 4. Catch wrong negatives | Set the rule: spent [X] to [Y], produced orders, but was negated. | Lists terms that may have been negated by mistake. | No one. Read only. |
| 5. Flag winners | Set the rule: CVR above [X]% and more than [two] orders from auto targeting. | Lists terms to add to manual campaigns. | No one. Read only. |
| 6. Preview the changes | Review the exact objects and values. | Shows each negative and each addition before submitting. | [Senior reviewer] approves. Needs write access. |
| 7. Write it down | Save the note for next Monday. | Summarizes what changed and what to watch. | The person who ran it. |
Step 1 sits first on purpose. A new hire who negates a term a teammate just promoted has undone someone else's work, and the log is where that shows up. Steps 2 to 5 are the analysis. Step 6 is the only one that writes, and it needs write access on your account. Step 7 is boring and it is the one teams skip.
Run it by hand first, in one chat, one step at a time. A skill built from a messy routine automates the mess. Run the SOP once, note every place the assistant needed a correction (wrong window, missing threshold, unclear output), and fix the SOP before you do anything else.
Three habits make the run cleaner. Name the object, meaning the ad account and campaign, right in the question. Give a time window and a comparison. Spell out the output you want, whether that is a table, a top-N list or a one-line takeaway.
Prompt: steps 2 to 5, read only
In ad account [account name], review search terms for the last [30] days. Show CTR, CVR, ACOS and orders. List terms that spent more than [X] with no orders and have not been negated. Then list terms that spent [X] to [Y], produced orders, and were negated, so I can check for wrong negatives. Then list terms from auto targeting with CVR above [X]% and more than [two] orders that belong in manual campaigns. Change nothing.
Prompt: step 6, preview before any change
From the lists above, show every negative keyword and every manual-campaign addition you would make: campaign, ad group, keyword, match type and bid. Do not submit anything. Wait for my confirmation.
Weekly Ads Report, Monthly Ads Report, Ads Structure Analysis and Product Diagnosis are four worked examples of a skill that someone already got right. Each one fixes the data it inspects, the order it works in and the shape of its answer. Read them the way a new hire reads your SOP.
| Official skill | You say | What it produces |
|---|---|---|
| Weekly Ads Report | "Give me last week's ads report" | Week-over-week KPIs, 7-day trends, anomalies and AI and automation activity, top movers, next-week action suggestions |
| Monthly Ads Report | "Generate last month's ads report" | Month-over-month and year-over-year KPI baselines, ad-group-level structural share, product and keyword performance, goal attainment, new-product detection |
| Ads Structure Analysis | "Analyze my advertising structure" | Spend and output by ad type and by manual versus auto, a diagnosis of structure imbalance, ACOS and CPA trends by section |
| Product Diagnosis | "Diagnose product performance" | ASIN and parent-ASIN ranking tiers, declining-product detection, variant comparison, ad eligibility and inventory checks |
Notice what repeats. A trigger phrase a person actually says. A fixed list of things to check. A fixed output, so Tuesday's report looks like last Tuesday's. Borrow all three.
To try one, name the skill you want, such as "I want the weekly ads report", and the assistant guides you through installing it. Connecting never installs skills on its own. In a new chat, ask the assistant to follow the instructions in the Xnurta skills repository. Search Term Traffic Diagnosis is also on the official list, so install it and compare it with your SOP. More on the full set in How an SOP becomes something an AI assistant can run.
Scenario, rules and output. Those are the three steps the assistant takes you through when you build one, and they map onto your SOP almost one to one.
If a step in your SOP cannot be sorted into one of the three, it is probably a habit, not a rule. Cut it or make it concrete.
In a client that supports skills, tell the assistant "I want to build a Skill." It guides you through three steps: describe the scenario, set the rules and define the output. Use your SOP's content for each of the three and answer what it asks.
Prompt: build the team's first skill
I want to build a Skill called Weekly Search Term Cleanup. Scenario: Every Monday I review search terms for one ad account at a time. I will name the ad account. Rules: Check the operation log for the last [14] days first, so we do not undo a teammate's change. Use the last [30] days of search terms. Flag terms that spent more than [X] with no orders and are not negated. Flag terms that spent [X] to [Y], produced orders and were negated. From auto targeting, flag terms with CVR above [X]% and more than [two] orders as candidates for manual campaigns. Never archive anything. Before any change, list every object and exact value and wait for my confirmation. Output: One table per flag type with campaign, search term, spend, orders, CVR and ACOS. Then a one-line takeaway, then the list of proposed changes. When you have drafted it, test it on [account name] with my real data.
Prompt: check the skill against your hand run
Run Weekly Search Term Cleanup on [account name] for the last [30] days. Compare its flags with the list I made by hand this week and tell me every difference.
Test it on real data, then compare the result with a run you did by hand. The assistant can test-run the skill on your real data while you build it, and you save it once you are satisfied. The second prompt above gives you a clean way to judge it: every difference is either a gap in the skill or a mistake in your hand run.
Then you choose who gets it. You can keep a saved skill private or share it within your organization, and teammates can install what you share. Keep it private while you iterate. Share it when two people run it on the same account and get the same flags. Keep the SOP as the page your team reads and the skill as the way the assistant follows it.
The same controls as without a skill. Reading performance, settings and the operation log changes nothing in your account. Edits need write access, and each kind of write has its own permission scope, so a connection that can edit ads cannot necessarily create campaigns.
Anything involving money, bids or archiving returns a preview first: which objects, and from what value to what value. Nothing is submitted until you confirm. Archiving cannot be undone, so pause a campaign if you only want it to stop. For how the read and write sides differ, see Read-only vs read-write MCP for Amazon advertisers.
The access rule
Generally available from 27 Oct for Sponsored Ads. Write access is turned on per account by your CSM.
FAQ
For every step: the data to pull, the time window, the threshold that triggers action and the person who confirms. Add a short list of things the process never does, such as archiving a campaign.
Yes, in a client that supports skills. Say "I want to build a Skill" and it guides you through describing the scenario, setting the rules and defining the output, then can test-run it on your real data and save it once you are satisfied.
No. Adding the connector only completes the connection. In a new chat, ask the assistant to follow the instructions in the Xnurta skills repository to install them.
Edits need write access, which is turned on per account by your CSM. Anything involving money, bids or archiving returns a preview first, and nothing is submitted until you confirm.
You can keep it private or share it within your organization. Teammates can install the skills you share.
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