Stop and Regenerate Controls
Let users halt a bad answer and ask again without losing the conversation.
What it adds
Stop and regenerate actions on an in-progress or completed AI response, with the prior context preserved.
What your agent is told to do
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What your agent is told to do
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Wire stop to an actual cancellation of the server-side run, propagated to the provider request, so generation ends rather than continuing invisibly.
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Keep whatever text arrived before the stop, store it marked as stopped by the user, and make that state visible in the transcript rather than deleting it.
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Build regenerate from the conversation state as it stood before the response being replaced, never from the abandoned partial output.
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Retain previous attempts and let the user move between them, so regenerating does not destroy an answer that was better than its replacement.
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Streaming AI Responses owns transport and incremental rendering. This entry owns the user-facing controls and the run lifecycle around them. Do not reimplement stream handling here.
Edge cases it handles
8
Edge cases it handles
8- Hiding incoming text without aborting the request leaves the model generating and the account paying. Stop must cancel the run at the server and at the provider where the provider supports it.
- Partial output that is silently discarded looks like a bug, and partial output shown as if complete is worse. Keep it, label it as stopped, and disable any action that treats it as a finished answer.
- Regenerating from the unfinished response feeds the model its own truncated text and produces a continuation rather than a fresh answer. Rebuild the request from the ancestor messages only.
- Usage accounting must reflect what actually happened: a stopped run consumes what it generated, and a regeneration is a new run, not a free retry. Reconcile against the provider's reported usage rather than assuming.
- A tool call that already wrote data, sent a message, or charged something cannot be undone by stopping. Detect completed side effects, surface them to the user, and never replay them on regenerate.
- Rapid repeated presses of regenerate must not launch parallel runs against the same message. Disable the control while a run is in flight.
- Stopping must leave the conversation in a state the user can continue from, with the input available and no orphaned pending row in the transcript.
- A run that has already finished server-side when stop is pressed should complete cleanly rather than being recorded as stopped.
Definition of done
8
Definition of done
8- Stop cancels the run at the server and the provider, and generation verifiably ends.
- Partial output is retained in the transcript, clearly marked as stopped, and cannot be mistaken for a complete answer.
- Regeneration rebuilds the request from prior context and never includes the abandoned partial response.
- Stopped runs and regenerations are accounted for accurately against real reported usage.
- Tool calls with completed side effects are surfaced and never re-executed by a regeneration.
- Repeated presses cannot start parallel runs, and previous attempts remain reachable.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
Streaming AI Responses
Streaming AI Responses
Show AI output as it is generated so long answers do not look frozen.
What it does
Incremental rendering of model output as it arrives, with a persisted authoritative copy once the stream closes.
How it works
- 1 Find the AI surfaces where the user waits on a long response and stream those. Short classification or extraction calls do not benefit and should stay as plain requests.
- 2 Buffer incoming bytes until they form complete characters and complete structural units before rendering, so partial output never appears as broken glyphs or half-open markup.
- 3 Treat the streamed text as provisional. When the stream closes, persist the provider's final message as the authoritative record and reconcile what is on screen against it.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/streaming-ai-responses
AI Support Triage
AI Support Triage
Summarise each incoming support request and estimate how urgent it really is.
What it does
An automatic summary, urgency estimate, and likely problem area attached to every inbound support request, with the evidence behind each.
How it works
- 1 Run triage as a background job on arrival, using the app's existing queue and retry behaviour. The ticket must be visible and workable in its raw form the moment it lands, whether or not triage has finished.
- 2 Produce three separate outputs — a short summary, an urgency level, and a likely problem area — and store each with the quoted source statements from the ticket that support it, so a human can check the reasoning.
- 3 Define urgency in terms of business impact: who is blocked, how many, whether money or data is at risk. Compute it from what the ticket describes, not from how the writer sounds.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-support-triage
AI Suggested Support Answers
AI Suggested Support Answers
Give support agents a grounded first draft instead of a blank reply box.
What it does
A draft reply composed for the agent from the ticket, the customer's account state, and the approved internal knowledge, with sources attached and no ability to send itself.
How it works
- 1 Ground every draft in retrieved material: the ticket thread, the account's real state, and articles from the approved knowledge set. Attach the sources used to the draft so the agent can open and check each one.
- 2 Load the draft into the agent's normal reply editor, unsent and fully editable. There is no path in this feature that sends a message to a customer without an agent pressing send.
- 3 Define the commitments the app is not allowed to make in a draft — refunds, credits, delivery dates, guarantees of a fix — and strip or refuse any draft containing them, leaving that part for the agent to write.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-suggested-support-answers
How it works
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Copy the link
Grab the Markdown instruction URL for this feature.
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Give it to your AI
Paste it into Claude Code, Cursor, v0, Lovable — whatever you build with.
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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.