AI Next Best Action
Suggest the most useful next step on a record, drawn only from actions the user can take.
What it adds
A suggestion panel on a record or workflow that proposes a next step, cites the facts behind it, and links to the action.
What your agent is told to do
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What your agent is told to do
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Build the candidate list first, in ordinary code: enumerate the actions that are valid for this record in its current state and permitted for this user, then let the model choose and rank from that list only. A suggestion the user cannot perform is worse than no suggestion.
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Assemble a compact, explicit fact set for the record — status, dates, owner, recent activity, outstanding obligations — and send only that. Do not send the whole record, unrelated customer data, or free-text notes that may contain personal information the feature does not need.
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Require the model to return the chosen action identifier plus the specific facts that support it, and render those facts beside the suggestion. A suggestion the user cannot audit will be ignored or, worse, trusted blindly.
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Present every suggestion as a proposal the user clicks to perform. Do not execute the suggested action automatically, and mark destructive, irreversible, or externally visible actions so they route through the app's existing confirmation step rather than a one-click accept.
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Recompute when the record's state materially changes, and invalidate the cached suggestion at the same moment. Do not recompute on every page view; that turns a modest per-record cost into an unbounded one.
Edge cases it handles
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Edge cases it handles
8- The model may name an action that does not exist or that this user lacks permission for. Validate the returned identifier against the candidate list and drop anything that does not match, rather than surfacing a dead control.
- When the supporting evidence is thin, the correct output is no recommendation. Give the model an explicit way to decline and show a plain empty state instead of manufacturing a weak suggestion to fill the panel.
- Suggesting an irreversible or high-risk action — deleting, cancelling, charging, notifying a customer — must never be a single click from the suggestion panel. Route it through the same review the app already requires.
- A record whose state changed after the suggestion was generated must not keep showing the stale advice. Tie the cached suggestion to a version of the record state and discard it when that version moves on.
- If the model times out, refuses, or returns output that does not parse into a known action, hide the panel entirely. A broken or apologetic suggestion box on every record erodes trust in the whole screen.
- Per-record generation multiplied across a list view can be ruinously expensive. Generate on the detail view or on explicit request, and cap how many suggestions a workspace can generate in a period.
- The explanation must describe observed facts, not invent history. Suggestions citing events that are not in the fact set are a defect, not a wording problem.
- When the model is unavailable, the surrounding record page must render normally with the panel absent, not blocked behind a pending request.
Definition of done
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Definition of done
9- Every suggestion resolves to an action that exists, is valid for the record's current state, and is permitted for the viewing user.
- Each suggestion displays the specific facts that support it.
- No suggested action is performed without an explicit user click, and high-risk actions still pass through the app's confirmation step.
- Weak evidence produces an explicit no-recommendation state rather than a speculative suggestion.
- A suggestion is invalidated and regenerated when the record's state changes, and is not regenerated on every view.
- Model failure, refusal, or unparseable output leaves the record page fully usable with no suggestion shown.
- Only the assembled fact set is sent to the provider, and generation volume is capped per workspace.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
AI Image Alt Text
AI Image Alt Text
Draft alternative text for uploaded images so screen readers get something useful.
What it does
A suggested alt attribute offered at upload time, editable and confirmable before the image is used.
How it works
- 1 Find every place the app accepts an image and currently stores an empty or absent alt attribute, and offer a suggestion at that point rather than in a separate cleanup screen.
- 2 Ask first whether the image is decorative. A decorative image takes empty alt text, and forcing a description onto it makes the page worse for the people the feature is meant to serve.
- 3 Pass the surrounding context — the page heading, the nearby caption, the purpose of the field — so the suggestion describes the image's role, not just its contents. Do not repeat an existing caption verbatim; a screen reader user would then hear the same sentence twice.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-image-alt-text
AI FAQ Generator
AI FAQ Generator
Produce short question and answer pairs from a document you have already approved.
What it does
A set of concise question-and-answer pairs generated from one nominated source document, each traceable back to the passage it came from.
How it works
- 1 Require the user to nominate a single approved source — a help article, a product page, a policy document — and generate only from that. Do not blend several documents or fall back to general knowledge when the source is thin.
- 2 Store each generated pair with a reference to the passage in the source that supports it, so a reviewer can confirm the answer without rereading the whole document.
- 3 Keep answers to a few sentences and link to the fuller section of the source for anything longer. An FAQ that restates the entire document is just a worse copy of it.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-faq-generator
AI Translation
AI Translation
Translate app content while preserving structure, placeholders, and product terminology.
What it does
A translation pipeline over the app's translatable content that keeps source and target linked, protects non-translatable tokens, and routes uncertain output to review.
How it works
- 1 Identify what is genuinely translatable and separate it from what is not. Extract placeholders, markup, URLs, identifiers, code, and proper names into protected tokens before generation and restore them afterwards.
- 2 Store every translation with a reference to the exact source version it came from. When the source changes, mark the translation stale and queue it for retranslation rather than leaving a silently outdated string in place.
- 3 Hold a per-language glossary of product terms and their approved renderings, and apply it to every request. A term that translates three ways across the app is worse than leaving it in the source language.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-translation
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.