Acting on recommendations
Up to ten ranked fixes per run, each with its measured reason and one to three steps, plus a playbook for every category.
How recommendations are made
The list is rebuilt every run. The numbers decide what's wrong; a model only writes the steps.
Gaps are detected in code. Each category checks the run's numbers for a clear, measurable gap.
Steps come from the evidence. A model writes one to three from what the engines said and cited for that gap.
Steps are checked before you see them, so they stay within the evidence and off competitors' properties.
Fixes rank by likely impact, and no single category crowds out the rest.
The rules every step follows
- Only channels you own or can earn: your site and docs, review sites, directories, communities, PR, guest posts and partners.
- Nothing on a competitor's property, and no invented domains, statistics or claims.
- Specific to the engine with the gap and to the monitor's persona and region.
- No shortcuts that don't earn answers, like keyword stuffing or schema tricks.
Whether AI crawlers can reach your site is a separate check: the site audit, on every plan.
Reading a recommendation
Earn citations from the sources AI trusts
Why?Only 12% of the citations AI gives you point to your own pages. Engines lean on ridereview.example and commutermag.example.
- Get Tarnwell City into the next ridereview.example commuter roundup, with your cold-weather range test results.
- Rank and category. Its place in the list and which playbook applies. New: first seen this run.
- Target. The metric this fix should move.
- Title. The gap in one line, in a fixed pattern per category.
- Why? The measured reason.
- How. One to three steps from what the engines said and cited.
- View in. Opens the evidence.
Overview shows the first three; the full list is under What to do next. Free shows your top two, and the rest are locked until Growth. Directional cards come from thin runs (few engines or questions), so treat them as leads to confirm on the next full run.
Categories at a glance
In typical rank order, though a big gap can outrank a smaller one above it.
Citations
Playbook and evidence
- In Sources by Engine, list often-cited third-party domains that never point to you. Start with the engine that cites you least.
- By type: get listed and reviewed on review sites and directories, pitch publications something new (like test data), answer community questions and build partner pages.
- Make your pages citable: the answer in the first paragraph, then specs, prices, test results and a date.
- Re-run once placements are live and check New and lost sources.
The citation targets skill turns this tab into a ranked outreach list.
Competitive
Playbook and evidence
- On each head-to-head question, read why the engines prefer them. It's usually stated outright.
- Publish a fair comparison page: who each option suits, specs side by side, where each wins. Engines lean on advice, not ads.
- Earn the proof they're credited with (reviews, case studies, awards) on the sources the engines cite.
- Add an alternatives page for buyers who start from their name.
Funnel
Playbook and evidence
- Awareness. These questions never name you, so answer the category: "best e-bike for a hilly commute" guides, how-to-choose pages and third-party roundups.
- Consideration. Comparison, alternatives, pricing and migration pages.
- Decision. Reliability, support, warranty, clear pricing, reviews and case studies.
Prompts
Playbook and evidence
- Copy the exact questions. Each one is a content brief.
- Find the page that answers each one plainly. Often there isn't one, or it's buried.
- Write or extend it: the answer first, evidence second, in the buyer's words.
- Link it from related pages, and get the answer onto the sources the engines cite for that question.
The content briefs skill drafts a brief for each question you're invisible or weak on.
Sentiment
Playbook and evidence
- Trace the quote: expand a question where it appears and check what that answer cites.
- Out of date? Post a dated update on the product page and release notes, and ask the cited source to refresh.
- True? Answer it with specifics: test data, a fair comparison or a customer story.
- Keep publishing. If you go quiet, buyers only hear what other sources say about you.
Strength
Playbook
- Keep the pages that earn the credit current (the ones cited on those questions).
- Extend to neighboring questions: win on ride comfort, then answer comfort for longer commutes.
- Bring the strength into comparison pages where you trail.
When the list is empty
If the tab says no standing gaps cleared the bar, that's a good result. Keep runs going so new gaps surface fast, and build on Strength cards.
Turn recommendations into work
A list nobody owns doesn't move a number. A routine that works:
Pick one or two per run, from the top unless a lower card is much cheaper to ship.
Give each an owner and a date, with the Why and How pasted into the ticket.
Ship, then re-run with Run now, the on-demand webhook or
trigger_geo_test_run. Re-runs use prompts.Check the deltas. Earned coverage can take a few runs to show.
Let an agent draft the fixes
On Growth and Enterprise, agents read recommendations over the MCP server. Use the Contentstack Canoe skills, or build an Agent OS content agent that drafts entries for review. Nothing publishes without your approval.