Suspense Boundary Strategy
Place loading boundaries so the page fills in usefully rather than all at once.
What it adds
A decision about where the interface is allowed to wait, so slow regions never hold up the parts that are ready.
What your agent is told to do
5
What your agent is told to do
5-
1
Map each screen into the regions that can be shown independently — the shell and navigation, the primary content, then secondary panels and counts — and let each one arrive on its own rather than waiting for the slowest.
-
2
Draw a boundary wherever a slow region would otherwise delay a fast one, and only there. A boundary per component fragments the page into a dozen separately twitching rectangles.
-
3
Start every request a region needs as early as the parameters are known, so the requests overlap instead of queueing behind whichever component happens to render first.
-
4
Give each boundary a placeholder with the same dimensions as its eventual content, so regions resolving in an unpredictable order do not push each other around the page.
-
5
This entry decides where the boundaries go and what the placement is trying to achieve; the appearance of the pending, empty, and refreshing states inside them belongs to Async Boundary Component. Do not define a second set of skeletons here.
Edge cases it handles
7
Edge cases it handles
7- Content already on screen must stay on screen during a refetch. Falling back to a placeholder for data the user is currently reading is a regression, not a loading state.
- Server-rendered markup and the client's first render must agree about which regions were pending, or the page will visibly reshuffle the moment it becomes interactive.
- Requests must not chain. A region that fetches a record, renders, then fetches that record's related items turns two round trips into a sequence, and the boundary hides the delay rather than removing it.
- Every boundary needs a matching failure containment from Error Boundary Pattern. A region that can be pending can also fail, and without a fallback the failure escapes to the nearest ancestor and takes healthy regions with it.
- Streaming a page in fragments changes when the document title, the metadata, and the response status can be decided. Settle those before the parts that stream, or a not-found record will be delivered inside a successful page.
- Keyboard focus and scroll restoration must account for content that arrives after the initial paint, or a user who tabs immediately will land somewhere that then moves.
- Boundaries around content above the fold should be few. The user is judging the page by how quickly the top of it settles, not by how many pieces it was split into.
Definition of done
9
Definition of done
9- Each screen resolves in named stages, with the shell and primary content never waiting on secondary regions.
- The number of boundaries is deliberate and documented per screen, not one per component.
- Requests for a screen's regions are issued in parallel, with no region waiting on another's response to begin.
- Refetching data leaves the currently visible content in place.
- Server and client agree on the pending regions, with no visible reshuffle on hydration.
- Every boundary is paired with failure containment from Error Boundary Pattern.
- Placeholders match the dimensions of their content, and regions resolving out of order cause no layout shift.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
AI Cost Budgets
AI Cost Budgets
Cap what AI features are allowed to spend before the bill arrives.
What it does
Monetary spending limits on AI work, scoped by workspace, feature, and time period, enforced before a run starts.
How it works
- 1 Find every place the app calls a model and route all of them through one accounting point that records estimated and actual spend against a scope. A budget that only covers the chat feature is not a budget.
- 2 Estimate the cost of a run from the size of its input before dispatching it, and refuse anything that would exceed the remaining budget on its own.
- 3 Reserve the estimate against the budget when the run starts, then reconcile to the real usage figures when it finishes, releasing whatever was over-reserved.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-cost-budgets
Multi-Model Routing
Multi-Model Routing
Send each AI request to the right model using rules you can read and test.
What it does
A deterministic routing layer that picks a model per request from task type, context size, latency budget, and data sensitivity.
How it works
- 1 Express routing as explicit, ordered rules over inputs the app can measure: task type, estimated context size, latency budget, and the sensitivity classification of the data involved. A rule set that can be read line by line can be reviewed and tested.
- 2 Make routing deterministic. The same inputs must always produce the same route, so a bad output can be reproduced and a rule change can be evaluated. Randomised or load-based selection turns every incident into guesswork.
- 3 Classify data before routing and refuse to route restricted content to any destination not approved for it. This check is a hard block, not a preference, and it must run before the request is assembled.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/multi-model-routing
SEO Setup
SEO Setup
Make your app findable — titles, meta, Open Graph, sitemap, robots.
What it does
The baseline SEO and social-preview setup every public app should have, and most skip.
How it works
- 1 Give every public page a unique, descriptive title and meta description. Find the app's layout and add a mechanism for each page to set them.
- 2 Add Open Graph and Twitter Card tags so shared links render a preview instead of a bare URL.
- 3 Generate a sitemap.xml covering every public, indexable page, and a robots.txt pointing at it.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/seo-setup
How it works
-
1
Copy the link
Grab the Markdown instruction URL for this feature.
-
2
Give it to your AI
Paste it into Claude Code, Cursor, v0, Lovable — whatever you build with.
-
3
It inspects, then implements
Your agent reads your existing app first, then adds the feature to fit it.
Works with your stack
These instructions are written to adapt. They tell the agent to detect your framework, match your existing design system, and reuse what you already have — rather than assuming a particular stack.
Need it tighter than that? Customize the feature and tell it exactly what you're running.