AI Release Note Generator
Turn the work that actually shipped into release notes a person can read.
What it adds
A drafting step that assembles internal and public release notes from the change records the app already tracks.
What your agent is told to do
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What your agent is told to do
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Find where the app already records completed work — merged changes, closed tickets, deploy records — and build the input set from those, scoped to a release or a date range. Do not ask the user to paste a changelog the system could assemble itself.
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Send only what the summary needs: change titles, descriptions, labels, and the area of the product affected. Never send full diffs, configuration files, credentials, customer names, or the contents of a private record the eventual reader is not entitled to see.
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Generate two detail levels from the same input set: an internal note that keeps identifiers, caveats, and rollback notes, and a public note written for someone who has never seen the codebase.
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Present the result as an editable draft with every line traceable to the change it came from, and require a human to publish it. Do not publish generated notes automatically; a wrong release note becomes a support queue, not a typo.
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Set a token and cost ceiling per generation, and split a large release into batches that are summarised and then merged. If the model refuses, times out, or returns a truncated draft, fall back to a plain grouped list of change titles and say the summary could not be generated.
Edge cases it handles
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Edge cases it handles
8- Work that is merged but sitting behind a disabled flag has not shipped. Filter on what is actually enabled in the target environment, or the notes will announce features nobody can find.
- Every generated line needs a link back to the change or ticket it came from, so a reviewer can check a claim without rereading the whole release.
- Dependency bumps, formatting passes, and internal refactors are noise in a public note. Exclude them unless they change something the user can observe, and keep them in the internal version.
- A change that was reverted, or deployed to only some regions or tenants, must not appear as shipped. Reconcile against the deploy record rather than the merge history alone.
- Internal and public audiences need different detail. A note that names internal services, incident numbers, or customer accounts must never be publishable without an explicit edit.
- A release with no user-visible changes should produce an honest empty state, not an invented summary of minor work.
- Regenerating a note must not discard edits a human already made. Offer the new draft alongside the edited one and let the user choose.
- If the release spans more changes than the cost ceiling allows, say which range was summarised rather than silently truncating the input.
Definition of done
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Definition of done
9- Release notes are drafted from the app's own change and deploy records with no manual paste step.
- Each generated line links to the source change that produced it.
- Internal and public versions exist separately and the public version excludes internal identifiers and non-user-visible work.
- Changes behind a disabled flag or subsequently reverted do not appear as shipped.
- Nothing publishes without a human approving the draft.
- A model refusal, timeout, or truncated response degrades to a plain list of change titles with an explanation.
- Each generation runs within a defined token and cost ceiling.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
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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 Knowledge Base Drafting
AI Knowledge Base Drafting
Turn a solved support issue into a help article draft a writer can finish.
What it does
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.
How it works
- 1 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.
- 2 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.
- 3 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.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-knowledge-base-drafting
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.