Multimodal Image Analysis
Let users ask questions about screenshots, photos, charts, and interface images.
What it adds
Image input on AI conversations, with safe downscaling, grounded answers, and defined retention of derived copies.
What your agent is told to do
5
What your agent is told to do
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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.
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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.
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Label and reference images explicitly when more than one is attached, so a question about the second chart is not answered from the first.
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Refuse identity claims and inferences about protected or sensitive attributes from a person's appearance, and define this refusal in the app rather than relying on the provider to enforce it.
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AI Chat Attachments owns upload, storage, scoping, and retention. This entry owns preparation and interpretation. Do not build a separate upload path for images.
Edge cases it handles
8
Edge cases it handles
8- Aggressive downscaling destroys exactly what users most often ask about: small interface text, axis labels, and error messages. Size against legibility, and offer a region crop rather than degrading the whole image.
- Questions inviting the model to identify a person or infer their age, ethnicity, health, or beliefs from a photograph must be refused with an explanation, not answered with a hedged guess.
- An answer that mixes what is on the pixels with what the model assumes is unfalsifiable. Require visible evidence to be stated separately from interpretation.
- With several images attached, an unlabelled reference is ambiguous. Number or name them in both the prompt and the answer so the user can tell which one is being described.
- Uploaded images and every derived copy, including thumbnails, downscaled versions, and cached crops, must inherit the conversation's access scope and be deleted on the same schedule as the original.
- Images containing credentials, personal documents, or payment details will be uploaded by users who did not think about it. Warn where it is plausible and never log image content or derived text into general application logs.
- Animated, multi-page, and very large images need a defined handling rule rather than an unhandled failure.
- When image input is unavailable, the feature must say so and fall back to text-only conversation rather than accepting the upload and ignoring it.
Definition of done
9
Definition of done
9- Images are reoriented, stripped of location and camera metadata, and downscaled without losing small text legibility.
- Answers separate what is visible in the image from what is inferred and say when the image is insufficient.
- Identity claims and sensitive-attribute inferences are refused with an explanation.
- Multiple images are labelled and referenced unambiguously in both the request and the answer.
- Derived copies inherit the conversation's access scope and are deleted with the original.
- Image content and extracted text never appear in general application logs.
- Unavailable image support degrades to text-only with a clear message rather than a silent no-op.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
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
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.