AI Knowledge Base Drafting
Turn a solved support issue into a help article draft a writer can finish.
What it adds
A structured, unpublished help article draft generated from a resolved ticket or a set of product notes, with unverified content marked and customer details removed.
What your agent is told to do
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What your agent is told to do
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Take a resolved ticket thread or a set of product notes as input and produce a draft in the app's existing article structure — title, summary, prerequisites, steps, related links — rather than one block of prose.
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Strip customer identity before the content is sent anywhere: names, addresses, account identifiers, order numbers, and anything else that identifies the person or their organisation. Remove it at the point the input is assembled.
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Mark the steps that were confirmed to resolve the issue separately from the ones that were tried and abandoned during troubleshooting. A draft that presents a failed experiment as instruction is worse than no draft.
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Pass the app's current feature names and interface labels in as reference material and require the draft to use them, so articles do not describe screens with names the product stopped using.
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Create the article in draft state only, in the app's existing publishing workflow. This brief produces long-form articles from solved issues; short question-and-answer pairs from an already-approved document belong to AI FAQ Generator.
Edge cases it handles
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Edge cases it handles
8- One customer's ticket becomes public documentation here. Any residual identifying detail — a company name in a log line, an email in a screenshot path — is a disclosure, so redaction must run before generation and be checked after it.
- Troubleshooting threads are full of dead ends. Steps that did not work must be excluded or clearly labelled, and the draft must state which sequence was actually verified to fix the problem.
- Stale terminology makes an article unusable even when the steps are right. If a label in the draft does not match anything in the current product, flag it for the writer rather than publishing it.
- Screenshots and interface captures cannot be generated. Mark the places one is needed with a note on what it should show, and leave the gap visible rather than describing an image that does not exist.
- Nothing generated here reaches customers without a human publishing it. Draft state is the default and there is no automatic publish path.
- A refusal, timeout, or malformed structure must leave no partial article behind. Either the full draft is created or the attempt is discarded with an error the requester can see.
- A ticket containing credentials, tokens, or configuration secrets must be refused as an input rather than redacted and used.
- Enforce a length ceiling and a per-workspace limit on drafting runs so a bulk import of resolved tickets cannot generate hundreds of articles at unbounded cost.
Definition of done
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Definition of done
9- Drafts follow the app's existing article structure rather than arriving as undifferentiated prose.
- Customer-identifying and confidential details are removed before generation and verified absent after.
- Verified resolution steps are distinguished from abandoned troubleshooting attempts.
- Product names and interface labels match the current product, with mismatches flagged for the writer.
- Places requiring a human-captured screenshot are marked with what the image should show.
- Articles remain in draft until a person publishes them, with no automatic publish path.
- Drafting runs are capped per workspace and produce no partial article on failure.
- 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 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
AI Reply Suggestions
AI Reply Suggestions
Offer a few short reply options that fit the current message or thread.
What it does
A small set of one-tap reply drafts generated from the visible thread, inserted into the composer for editing before sending.
How it works
- 1 Generate suggestions from the visible thread only, and only when the last message is from someone other than the user. Suggesting a reply to the user's own message is noise.
- 2 Insert the chosen suggestion into the composer as editable text. Do not send on tap, however short the reply, because a one-tap send makes every model error a message the user cannot recall.
- 3 Require the options to differ in intent, not in wording — for example accept, decline, and ask for more detail. Three paraphrases of the same sentence give the user nothing to choose between.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-reply-suggestions
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.