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Human Review

CommunityPopular
petergyang
human-review

Open an HTML file, Markdown file, or localhost page in the browser so the user can edit text directly and leave comments on specific parts, then send all edits and comments back to you. Use after writing or updating something the user will read — specs, plans, reports, newsletter drafts, landing pages, slide decks, and locally running web pages.

Overview

Publisherpetergyang
Repositoryhuman-review
Skill namehuman-review
Stars
1.3K
Forks
102
Bundled files
18
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 18 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by petergyang on GitHub. Read the source before you install it.

Installation

Install the Human Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/petergyang/human-review.git /tmp/human-review
mkdir -p .claude/skills
cp -r /tmp/human-review/src .claude/skills/human-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Human Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Human Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Human Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

human-review

The user reviews your HTML, Markdown, or localhost page in a real browser: they fix small things by typing, select anything to comment on it, and send you the whole batch at once.

Markdown files open rendered. Their quotes and edits reference the rendered text, and the file itself is never touched — apply every change to the Markdown source, keeping its formatting syntax.

The loop

  1. Write or update the HTML or Markdown file, or start the local page being reviewed.

  2. Open it for the user:

    sh
    npx -y human-review path/to/file.html

    For a page served by a local development server, open the real route instead of recreating it as a separate HTML file:

    sh
    npx -y human-review http://localhost:3000/wiki
  3. Wait for feedback. This command blocks until the user hits Send in the browser, then prints their batch and exits:

    sh
    npx -y human-review poll path/to/file.html

    The command exits only when the user clicks Send or closes the review. There is nothing to re-run, no interval to poll on, and no --timeout to add. It survives the local server restarting, and feedback is saved even if the poll dies, so nothing is ever lost. How you wait depends on your harness:

    • Claude Code: run it with run_in_background: true and end your turn. Claude Code wakes you with the output the moment the command exits.

    • Codex, Cursor, and everything else: run it in the foreground, inside your active turn, and stay on it until it prints feedback or closed. Do not detach it or start it as a background session: nothing wakes you when a detached command finishes. While the review is active:

      • If the user sends a message, answer it as commentary and immediately resume the foreground poll in the same turn. Do not send a final response until the poll returns feedback or closed — a final response ends the turn and kills the wait.
      • If your shell tool caps command duration, pass --timeout a little under the cap and run bounded polls back to back in the same active turn until one returns feedback or closed.

      Know the limit: this is reliable only while your turn stays active. A turn that has already ended is not woken when the user hits Send; the user has to message you, and you then run status and poll to pick the batch up. There is no integration that resumes an ended task when the poll exits.

    If it prints {"status":"closed"}, the review is over: the user ended it, closed the tab, or never had one open (reason says which). Stop and do not start another poll. unsent counts feedback they left behind; if it is not zero, tell the user in one line that it is kept and they can restore or discard it next time. {"status":"superseded"} means a newer poll of yours owns the wait — stop this one silently. {"status":"timeout"} only appears after 12 hours; run status and start the wait again if the review is still open.

  4. Apply what comes back, then start the next background poll. --ack clears the batch you just handled:

    sh
    npx -y human-review poll path/to/file.html --ack

Repeat 3–4 until the user says they are done.

Not sure whether feedback is already waiting — say, at the start of a new turn with no poll running? This answers instantly without blocking:

sh
npx -y human-review status path/to/file.html

It prints {"status": "feedback-waiting"} when a batch is ready for a poll, plus counts of unsent comments and edits still in the browser.

What you get

One batch covers every page the user visited, grouped by file or localhost URL.

json
{
  "status": "feedback",
  "pages": [
    {
      "file": "/abs/path/to/page.html",
      "edits_saved": true,
      "comments": [
        { "id": "c_1", "kind": "selection", "quote": "the exact text they selected",
          "anchor": { "prefix": "...", "quote": "...", "suffix": "..." },
          "feedback": "what they want changed" }
      ],
      "edits": [
        { "label": "Problem body", "kind": "edited",
          "before": "the original wording",
          "after": "their exact new wording",
          "after_html": "their exact new wording with <strong>formatting</strong>" }
      ]
    }
  ],
  "overall_note": "feedback not tied to any one page"
}

Rules

  • edits are changes the user already made. after is their exact wording — carry it across verbatim and never revert it. If the HTML was generated from something else (MDX, Markdown, a template), apply after to the source too, or their fix disappears on the next build.
  • edits_saved: true means those edits are already in the file on disk. Plain HTML files autosave as the user types, so your copy of the file is stale. Re-read the file before touching it and make targeted changes only; never regenerate it from what you wrote earlier, or their work disappears. edits_saved: false (Markdown, localhost pages, self-rendering HTML) means the edits exist only in this batch — apply them to the source yourself.
  • An edit with kind: "deleted" means the user removed that whole block: delete it from the source too, without asking why.
  • An edit marked truncated: true had its text cut at 200k characters; read the block from the page itself rather than from after_html.
  • When before_html/after_html are present, the user changed formatting, not just words — bold, italic, underline, links. Use the HTML version to carry the formatting into the source, translated to its syntax (e.g. <strong>** in Markdown/MDX).
  • A page with kind: "url" was edited directly in the review UI. Its file and url fields name the localhost route, not a writable file. Find the matching project source (such as MDX, TSX, or a template), apply every edit and deletion there, then acknowledge so the route reloads. Never write the rendered HTTP response back into the app.
  • When an edit's after_html contains <img src="assets/...">, the user pasted an image: the file already exists in an assets/ folder next to the reviewed file. Keep that relative path — in Markdown, reference it as ![](assets/...). Never regenerate or inline the image.
  • On a localhost page, a pasted image arrives under staged_assets. Copy its local path into the app's appropriate asset folder, replace the temporary preview URL in after_html, and preserve the image at the user's insertion point. Never leave the temporary preview URL in source.
  • An edit with kind: "moved" means the user relocated that whole block. Reposition it in the source without rewriting its content: it now sits right after the block whose text starts with moved_after, and right before the block whose text starts with moved_before (both are clipped to 90 characters and may end in ). An empty moved_after means it is now the first block in its container.
  • Find each comment by its quote. It is the rendered text the user selected, so in Markdown or templated HTML it may span formatting syntax or tags; anchor.prefix and anchor.suffix give the surrounding text to disambiguate.
  • kind: "element" points at a whole block, so quote is its label, not body text.
  • Copy any staged_assets files before you ack: --ack deletes them.
  • A batch with only an overall_note has an empty pages array.
  • Fix every page in pages, not just the first.
  • Do not write a reply. There is no chat. The user sees your work when the page reloads, which happens on its own the moment you save the file.

Better edit labels (optional)

Name the sections you author and the user's edit list uses your names instead of guessing from the DOM:

html
<p data-block="Problem body"></p>
<div data-container="Metrics callout"></div>

data-block names a region for the edit list. data-container also makes the block clickable as a comment target.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Human Review AI skill do?

Open an HTML file, Markdown file, or localhost page in the browser so the user can edit text directly and leave comments on specific parts, then send all edits and comments back to you. Use after writing or updating something the user will read — specs, plans, reports, newsletter drafts, landing pages, slide decks, and locally running web pages.

Why use Human Review on TypingMind?

Because you install it once and use it with any model. Human Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Human Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/petergyang/human-review/tree/main/src. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Human Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Human Review?

As many as you like. As long as a model supports skills, you can use Human Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Human Review AI skill free?

Yes. It is published on GitHub by petergyang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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