Meta tags and on-page content Optimize meta tags and content with ChatGPT dots
Optimizing meta tags and on-page content with a ChatGPT dot means splitting the work in two: the dot finds the resources whose meta fields are failing, and a supervised ChatGPT conversation previews and applies the StoreSEO rewrite.
Last updated: October 2026
Set up ChatGPT dots for StoreSEO
Skip this if ChatGPT dots is already connected. The full guide, with the alternatives, is on the ChatGPT dots page.
- 1
Create the StoreSEO app in ChatGPT
OpenAI's help center says plugins are shared across dots and ChatGPT, so you set StoreSEO up once. In ChatGPT on the web, turn on Developer mode under Settings, Security and login, open Plugins, select the plus button and create an app named StoreSEO with this MCP server URL and OAuth. Sign in when the browser asks: pick your Shopify store and approve access. If ChatGPT already has the StoreSEO app, skip this step.
URLhttps://mcp.storeseo.com/mcp
- 2
Make sure your dot can see it
Open your dot's profile, then Customize and Plugins, and check StoreSEO is connected. Then give your dot a first task that names StoreSEO.
PromptUsing StoreSEO, show me my store's SEO score breakdown.
How does this work in ChatGPT dots?
Meta rewriting is the job where a timer is least useful and a human is most useful, so the useful dot pattern is a hand-off. Your dot runs a scheduled check that calls storeseo_start and storeseo_get_resource_seo on the products, collections or pages you point it at, and reports which have a missing or too-short meta description, no focus keyword in the title or an empty AI snippet. That report costs nothing but reads. It arrives with a short list of the resources worth fixing first.
The rewrite itself happens in a regular ChatGPT conversation using the same StoreSEO plugin. There you ask for storeseo_preview_resource_optimization on one resource, which makes StoreSEO write the meta title, description, tags, URL handle, FAQs and AI snippet server-side and projects the new score without saving anything. Previews spend AI Content Optimizer credit whether or not you apply them, so the agent should tell you the cost before it generates. When the handle would change, you see the old and new URL, because applying creates a redirect. Then storeseo_apply_resource_optimization writes only the parts you approved, and ChatGPT shows its own confirmation for that write.
Do not put the preview on the schedule. A weekly task that previews ten products spends credit ten times a week on drafts nobody has read, and drafts expire after an hour anyway. storeseo_get_ai_optimization_settings is a fine read for the dot to include, because it lets the report say what StoreSEO already generates automatically for new products, but changing those settings with storeseo_update_ai_optimization_settings is a decision for a conversation.
-
You: Using StoreSEO, preview better meta for the Linen Shirt product. Keep the URL handle.
- storeseo_start read-only
- storeseo_get_resource_seo read-only
-
ChatGPT dots: The meta description is 41 characters and the focus keyword is not in the title. A preview spends AI credit but writes nothing. Shall I generate one?
-
You: Yes, generate it.
- storeseo_preview_resource_optimization preview
-
ChatGPT dots: Here are the new title and description, projected to lift the score. Apply the meta only and leave the FAQ?
-
You: Yes, meta only.
- storeseo_apply_resource_optimization needs approval
What to ask ChatGPT dots
Every Friday, use StoreSEO to list products and pages whose meta description is missing or too short. Report only, no previews.
Preview a new meta title and description for the product Linen Shirt, keep the current URL handle, and tell me the credit cost first.
Apply the previewed meta description but skip the tags and the FAQ.
- Optimize the meta title and description for my five lowest-scoring products. Show me the previews before you apply anything.
- Preview a new meta title, description and FAQ for the collection Summer Dresses, and keep the current URL handle.
- Apply the meta from that preview but skip the FAQ.
- Which of my pages have no meta description? Draft one for each and wait for my approval.
- What does StoreSEO optimize automatically for new products right now?
- Turn on automatic meta and alt text for new products only. Tell me what that will spend first.
What StoreSEO does: meta tags and on-page content
StoreSEO generates the content server-side: meta title and description, tags, a keyword-led URL handle, FAQs and an AI snippet. The agent shows you the draft and the projected score change before anything is saved, then applies all of it or only the parts you approve.
Requires: Generating a preview spends AI Content Optimizer credit; applying a preview is free.
- 1
Read the current state
The agent reads the resource's SEO record so it knows which fields exist, which fail and what the preview will add.
- 2
Generate a preview
StoreSEO writes the meta title, description, tags, URL handle, FAQs and AI snippet and projects the new SEO score, plus the GEO score for products. Nothing is saved yet. Preview spends credit whether or not you apply it.
- 3
Show you the draft
The agent presents the generated text and the score change. When the handle changes it shows the old and new URL and tells you a redirect will be created.
- 4
Apply what you approve
After your yes it applies everything, or only the parts you chose, for example the meta but not the FAQs. Skipped fields stay available from the same draft for an hour.
- 5
Report the new score
The apply call returns the recomputed score and the remaining checklist, so the agent tells you what changed and offers the next most useful fix.
Meta tags and on-page content reference
| Generated fields | Meta title, meta description, tags, URL handle, FAQs, AI snippet |
|---|---|
| Resource types | Products, collections, pages and articles (collections have no meta tags or tags axis in auto settings) |
| Who writes the copy | StoreSEO, server-side. The agent never authors meta, FAQs or handles itself |
| Cost | Preview spends AI Content Optimizer credit; apply is free; a new preview spends again |
| Draft lifetime | One hour after the preview |
| URL handle | Applying a new handle changes the live URL and creates a redirect from the old one; a handle already in use is dropped automatically |
| Partial apply | Apply a subset of axes, or skip individual fields such as the handle |
| Auto optimization | Optional settings that generate content for newly synced resources; only future syncs, nothing is backfilled |
| Auto settings plan | Configurable on any plan; switching an auto toggle on needs a paid plan and no active trial |
Rules ChatGPT dots follows
- The agent previews first and applies only after you confirm the previewed content.
- When a handle changes, you see the old URL and the new URL before the apply call, because applying creates a redirect.
- A request like optimize my worst five products authorizes the previews; the agent should remind you that previews spend credit even if you do not apply them.
- Turning on auto optimization spends credit on every future sync, so the agent proposes the exact sections and waits for your yes.
- Product title, focus keyword and description body are not written by this job; the description has its own tool in the AI search job.
In ChatGPT dots
A dot can run on a timer, and a preview spends credit each time it runs. Keep the scheduled task to storeseo_get_resource_seo reads and leave storeseo_preview_resource_optimization and storeseo_apply_resource_optimization to a supervised chat. StoreSEO tells the agent to name the cost and wait for your yes, but that is an instruction, and the hard stops are your plugin's write confirmation and your dot's custom rules. If your plan only gives ChatGPT read access to connected servers, previews may be all you can do from ChatGPT, and the apply step moves to the StoreSEO app.
What runs without asking. Reads such as SEO scores, store listings, settings and Google reports run straight away. Generating a preview spends AI credit but writes nothing, and StoreSEO tells the agent to say what a generation will cost before it runs one. Applying content, optimizing images, changing settings, publishing llms.txt or agents.md, writing a product description and deleting anything wait for your yes in the conversation. That yes is an instruction the agent follows, not a lock on the server, so your client's own tool-approval setting is the hard stop.
Questions
Should I let my dot preview meta tags on a schedule?
Not as a rule. Each preview spends AI Content Optimizer credit and expires after an hour, so a recurring preview pays for drafts nobody reviews. Schedule the check that finds weak meta, and preview from a chat when you are ready to read the result.
Does the dot write the meta copy itself?
No. StoreSEO generates the meta title, description, tags, handle, FAQs and AI snippet server-side. The dot asks for the preview, shows you what came back and applies the parts you approve.
Does previewing an optimization change my product?
No. A preview generates the content and projects the score without saving anything. It does spend AI Content Optimizer credit, and applying the draft afterwards is free.
What happens to the old URL when the handle changes?
Applying a new URL handle updates the live URL and StoreSEO creates a redirect from the old one, so existing links keep working. The agent should show you both URLs before it applies the change.
Can I apply only part of a preview?
Yes. The apply step takes the axes you approved, and individual content fields such as the URL handle can be skipped. Skipped parts stay available from the same draft for one hour.
Does auto optimization fix my existing products?
No. Auto optimization only acts on resources synced or updated after you turn it on. Existing products are fixed with the preview and apply steps in this job.
Will StoreSEO change my product title?
No. This job writes the SEO meta title, not the storefront product title. The product title is edited in Shopify admin.
Keep going
Meta tags and on-page content with other agents
More ChatGPT dots guides