AI FAQ Generator
Produce short question and answer pairs from a document you have already approved.
What it adds
A set of concise question-and-answer pairs generated from one nominated source document, each traceable back to the passage it came from.
What your agent is told to do
5
What your agent is told to do
5-
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.
-
4
Compare new pairs against the existing set before saving, and merge or discard questions that ask the same thing in different words rather than accumulating near-duplicates.
-
5
Record the version of the source each pair was generated from, and mark pairs as out of date when the source changes rather than silently rewriting text a person already approved.
Edge cases it handles
8
Edge cases it handles
8- Any claim not present in the source is a fabrication, however reasonable it sounds. Drop pairs that cannot be traced to a passage instead of publishing them with a caveat.
- Generating from a document without generating for an audience produces questions nobody asks. Constrain the set to what a customer would plausibly type into search, and let the reviewer delete the rest easily.
- Long answers defeat the format. Enforce a length limit in the output and link out for detail rather than truncating mid-sentence.
- Overlapping questions clutter the list and split search results. Deduplicate on meaning, not on exact string match.
- When the source is edited, existing pairs must be flagged as stale and offered for regeneration. Leaving them unmarked means the FAQ quietly contradicts the document it came from.
- A short, structural, or mostly visual source yields nothing useful. Return an empty result with an explanation rather than padding the list.
- Refusals, timeouts, and malformed structured output must leave the existing approved pairs untouched.
- This feature generates short pairs from an approved document; producing full articles from solved support issues belongs to AI Knowledge Base Drafting, and the two must write to different content types.
Definition of done
9
Definition of done
9- Every pair traces to a passage in the single nominated source.
- Claims absent from the source are dropped rather than published.
- Answers respect a length limit and link to fuller guidance in the source.
- Near-duplicate questions are merged or discarded before saving.
- Pairs are versioned against the source and marked stale when it changes.
- An unsuitable source returns an empty result with an explanation.
- Failed generation leaves previously approved pairs unchanged.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
Multimodal Image Analysis
Multimodal Image Analysis
Let users ask questions about screenshots, photos, charts, and interface images.
What it does
Image input on AI conversations, with safe downscaling, grounded answers, and defined retention of derived copies.
How it works
- 1 Prepare images before they are sent: correct orientation, strip location and camera metadata, and downscale to the smallest size that still keeps small text and fine detail legible.
- 2 Require the answer to distinguish what is visible in the image from what is inferred, and to say when the image is too low in quality to support a conclusion.
- 3 Label and reference images explicitly when more than one is attached, so a question about the second chart is not answered from the first.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/multimodal-image-analysis
AI Image Captioning
AI Image Captioning
Describe images so they can carry a visible caption and be found by search.
What it does
A generated description stored per image, offered as a draft caption and indexed for search.
How it works
- 1 Store the generated description in its own field and decide explicitly whether each surface shows it, indexes it, or both. Do not write it into the alt attribute, which belongs to AI Image Alt Text and answers a different question.
- 2 Offer the description as a draft caption the user can accept or rewrite, and leave any caption a human already wrote untouched unless they explicitly ask for a replacement.
- 3 Index the description alongside the image's existing metadata so images become findable by what is in them, and reuse the app's existing search infrastructure rather than adding a parallel one.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-image-captioning
AI Changelog Drafting
AI Changelog Drafting
Turn merged work into a changelog draft written for customers, not for engineers.
What it does
A grouped, customer-facing changelog draft generated from merged work items or release notes for a nominated release, held for review before publishing.
How it works
- 1 Take the set of work items belonging to one nominated release as input, and require each item to carry a shipped marker before it is eligible. Unreleased and reverted work must be excluded at the input stage, not filtered out of the prose afterwards.
- 2 Rewrite each item as the outcome a customer notices rather than the change that was made, and keep a link from every drafted line back to the underlying item so a reviewer can check it.
- 3 Group related items under headings the reader would recognise, and keep fixes as their own visible section rather than absorbing them into a feature summary.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-changelog-drafting
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.