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Stop copying AI-written passages into chat to request edits. Review HTML documents visually in VS Code, leave comments on selected text, and keep replies in the same file. With the Agent Skill, AI agents can read your feedback, revise documents, and mark changes for review.
I'm the developer of Agentic HTML Visual Editor, a VS Code extension I built to make reviewing AI-generated documents easier.
Why I built it
As I started delegating more work to AI agents, I found myself spending more time reviewing their research reports and design notes than writing them.
The frustrating part wasn't reading the documents. It was requesting changes.
Every time I wanted something changed, I had to find the relevant passage, copy it into chat, explain what I wanted, and rely on the agent to locate that passage in the original document.
I was already using HTML instead of Markdown for richer document layouts, but that only solved the readability problem. Feedback and decisions were still scattered across chat history.
What I built
I wanted to leave feedback directly where I was reading, so I built a visual HTML editor for VS Code.
Here's how it works:
Ask an AI agent to generate a research report or design note as HTML.
Open it in the visual editor and leave comments on specific passages, or edit the text directly.
Save the file and ask the agent to review it. With the companion Agent Skill, it can read your comments, reply, and revise the document.
Review the agent's replies and proposed changes in the same editor, accepting or rejecting marked changes.
Comments and replies are stored directly in the HTML file, so the conversation stays attached to the document rather than getting lost in chat.
My goal was to make the next instruction to the agent as simple as:
"I've made changes; please review them."
I'd love your feedback
How do you currently review documents generated by AI agents?
Do you find yourself copying passages into chat to request changes, or have you found a better workflow?
No comment highlights available yet. Please check back later!
About Agentic HTML Visual Editor on Product Hunt
“Review AI-written docs visually in VS Code”
Agentic HTML Visual Editor was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #5 on the daily leaderboard. Stop copying AI-written passages into chat to request edits. Review HTML documents visually in VS Code, leave comments on selected text, and keep replies in the same file. With the Agent Skill, AI agents can read your feedback, revise documents, and mark changes for review.
Agentic HTML Visual Editor was featured in Open Source (69k followers), Developer Tools (521.5k followers), Artificial Intelligence (481.6k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 269.6k products, making this a competitive space to launch in.
Who hunted Agentic HTML Visual Editor?
Agentic HTML Visual Editor was hunted by Yuya Miyamoto. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Agentic HTML Visual Editor stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Yuya Miyamoto
Hey Product Hunt!
I'm the developer of Agentic HTML Visual Editor, a VS Code extension I built to make reviewing AI-generated documents easier.
Why I built it
As I started delegating more work to AI agents, I found myself spending more time reviewing their research reports and design notes than writing them.
The frustrating part wasn't reading the documents. It was requesting changes.
Every time I wanted something changed, I had to find the relevant passage, copy it into chat, explain what I wanted, and rely on the agent to locate that passage in the original document.
I was already using HTML instead of Markdown for richer document layouts, but that only solved the readability problem. Feedback and decisions were still scattered across chat history.
What I built
I wanted to leave feedback directly where I was reading, so I built a visual HTML editor for VS Code.
Here's how it works:
Ask an AI agent to generate a research report or design note as HTML.
Open it in the visual editor and leave comments on specific passages, or edit the text directly.
Save the file and ask the agent to review it. With the companion Agent Skill, it can read your comments, reply, and revise the document.
Review the agent's replies and proposed changes in the same editor, accepting or rejecting marked changes.
Comments and replies are stored directly in the HTML file, so the conversation stays attached to the document rather than getting lost in chat.
My goal was to make the next instruction to the agent as simple as:
"I've made changes; please review them."
I'd love your feedback
How do you currently review documents generated by AI agents?
Do you find yourself copying passages into chat to request changes, or have you found a better workflow?