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Reimagine It Extract

Community
Kayforkind
reimagine-it-extract

Emit the content signals reimagine-it reads from an HTML file — title, anchors, proper nouns, dates, numbers, emails, links, source hex colors, and the derived palette — as JSON without generating a redesign. Use when the user says /reimagine-it extract, "what does the engine see in this page", "extract the palette", "pull the facts from this page", or wants content analysis for research, migration, or design-system work. CLI: npx reimagine-it extract -i page.html -o signals.json. Part of the reimagine-it Content-Derived Design suite.

Overview

PublisherKayforkind
Repositoryreimagine-it
Skill namereimagine-it-extract
Stars
211
Forks
31
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Reimagine It Extract 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.
    https://github.com/Kayforkind/reimagine-it/tree/main/skills/reimagine-it/extract
  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/Kayforkind/reimagine-it.git /tmp/reimagine-it
mkdir -p .claude/skills
cp -r /tmp/reimagine-it/skills/reimagine-it/extract .claude/skills/reimagine-it-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reimagine It Extract 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 Reimagine It Extract 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 Reimagine It Extract 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.

/reimagine-it extract

Parent: ../SKILL.md — the full Content-Derived Design engine. This sub-skill handles only the extraction surface — the honesty layer the whole method stands on.

The redesign is only as honest as its extraction. This verb emits exactly what the engine reads, as JSON, without generating anything: title, profile, density, derived palette, anchors, proper nouns, headings, dates, numbers, emails, links, and source hex colors. Every extracted fact exists in the source — property-tested against hostile and malformed input.

Usage

bash
npx reimagine-it extract -i page.html -o signals.json
cat page.html | npx reimagine-it extract -o -        # stdin → stdout
npx reimagine-it extract -i page.html --full -o signals.json  # + prose

Payload shape (default):

json
{
  "source": "page.html",
  "title": "…",
  "profile": "restaurant | saas | civic | …",
  "density": "sparse | medium | dense",
  "palette": { "ground": "…", "accent": "…", "muted": "…", "surface": "…", "ink": "…" },
  "anchors": ["…"],
  "properNouns": ["…"],
  "headings": ["…"],
  "dates": ["…"],
  "numbers": ["…"],
  "emails": ["…"],
  "links": ["…"],
  "sourceHex": ["#6B3A2A"],
  "counts": { "paragraphs": 4, "listItems": 16 }
}

--full adds paragraphs and items (the raw prose arrays).

Procedure

  1. Run it before any redesign when the user asks "what would you even use from this page?" — the JSON answers with the engine's actual inputs.
  2. To audit honesty: every dates, numbers, emails, and links entry must be findable in the source. Nothing else is allowed to appear.
  3. Use it for migration/research: the payload is a stable, typed summary of a page's content — no redesign attached.

Must not

  • Add facts not present in the payload to any downstream summary
  • Present the derived palette as colors the source declared — hex colors in sourceHex were in the source; the rest is derivation
  • Round or "clean up" extracted numbers and dates; they are quotes

Part of reimagine-it — MIT.

Frequently asked questions

What does the Reimagine It Extract AI skill do?

Emit the content signals reimagine-it reads from an HTML file — title, anchors, proper nouns, dates, numbers, emails, links, source hex colors, and the derived palette — as JSON without generating a redesign. Use when the user says /reimagine-it extract, "what does the engine see in this page", "extract the palette", "pull the facts from this page", or wants content analysis for research, migration, or design-system work. CLI: npx reimagine-it extract -i page.html -o signals.json. Part of the reimagine-it Content-Derived Design suite.

Why use Reimagine It Extract on TypingMind?

Because you install it once and use it with any model. Reimagine It Extract 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 Reimagine It Extract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Kayforkind/reimagine-it/tree/main/skills/reimagine-it/extract. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Reimagine It Extract?

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 Reimagine It Extract?

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

Is the Reimagine It Extract AI skill free?

Yes. It is published on GitHub by Kayforkind 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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