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Replica Diff

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Jakeschincariol
replica-diff

Compares an app clone against the original: a feature parity score from the feature matrix (weighted by must, should, could) with the missing list in build order, plus a screenshot layout diff that ignores colour so a rebrand does not count against you. Two standard-library Python tools. Use when the user says "how close is my clone", "compare it to the original", "what's missing", "parity check", "diff the screens", "is it ready", or after /replica-test.

Overview

PublisherJakeschincariol
Repositoryreplica-skill
Skill namereplica-diff
Stars
1.9K
Forks
275
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Replica Diff 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/Jakeschincariol/replica-skill/tree/main/replica-diff
  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/Jakeschincariol/replica-skill.git /tmp/replica-skill
mkdir -p .claude/skills
cp -r /tmp/replica-skill/replica-diff .claude/skills/replica-diff
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Replica Diff 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 Replica Diff 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 Replica Diff 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.

replica-diff

Two tools in this folder, both standard-library Python, no installs:

bash
python3 parity.py replica/features.csv                         # feature parity + missing list
python3 imgdiff.py replica/screens/S07.png replica/clone-screens/S07.png --out diff-S07.png
python3 imgdiff.py a.png b.png --json > replica/diffs/S07.json # for parity.py --visual
python3 parity.py replica/features.csv --visual replica/diffs/*.json --markdown > replica/parity.md

What parity means here

Parity means it does the same job, not that it looks the same. The feature score is the number that matters: can a user do everything they could do in the original. The layout score checks structure (is the information in the same places, in the same hierarchy), because that is what makes a switcher feel at home. It deliberately ignores colour, because replica-brand changes every colour on purpose. Do not chase pixel parity with the original. Its exact look is its trade dress, and it changes before launch.

Step 1: feature parity

Make sure replica/features.csv is current: every row's clone column is yes, partial (with a note), no, or skip (with a reason). Then:

bash
python3 parity.py replica/features.csv

It weights must 3, should 2, could 1, counts partial as half, leaves out skip rows and rows you added that the original does not have, and prints: the score, must-haves done of total, each area weakest first, and the missing list in build order. Must-haves not done means not shippable, and it says so.

Step 2: layout diff

For each key screen, take two screenshots at the same viewport (1440x900 desktop, 390x844 mobile) in the same state (same data shape, same tab open, logged in the same way). The original's come from public pages or the user's own account, saved in replica/screens/. The clone's go in replica/clone-screens/.

bash
python3 imgdiff.py replica/screens/S07.png replica/clone-screens/S07.png --out replica/diffs/S07.png

Layout mode (default) turns both into edge maps, cuts them into a grid, and compares where things are, scoring only cells with something in them. It reports the score (matches 90+, close 75+, partly 50+, different), the regions that differ (in the original's pixel coordinates, biggest first), and a height difference if the clone's page is much longer or shorter. Retina and non-retina screenshots compare fine: both are scaled to the same width.

--mode pixel is exact comparison. Use it for your own regressions (clone today against clone last week), not against the original.

Step 3: behaviour diff

Walk each flow in both apps and compare what the scores cannot see: clicks to finish the core flow, what happens on errors, what is remembered between visits, what emails arrive. Fewer clicks than the original is a win. Write each difference as: flow, original does, clone does, fix or keep.

Step 4: the report

replica/parity.md: overall score, feature score, layout score per screen, missing features in build order, behaviour differences, and a verdict:

  • not shippable: any must-have missing, or any open S1 bug
  • shippable: all must-haves done, feature score 80+, no open S1 or S2
  • better than the original: shippable, plus fixes from replica-entrepreneur. This is the goal. A straight copy has no reason to exist.

Give honest numbers. A clone at 62% is at 62%.

Output

replica/parity.md, the diff images, and the top five things to build next. Then /replica-build for the gaps, or /replica-entrepreneur if parity is there.

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 Replica Diff AI skill do?

Compares an app clone against the original: a feature parity score from the feature matrix (weighted by must, should, could) with the missing list in build order, plus a screenshot layout diff that ignores colour so a rebrand does not count against you. Two standard-library Python tools. Use when the user says "how close is my clone", "compare it to the original", "what's missing", "parity check", "diff the screens", "is it ready", or after /replica-test.

Why use Replica Diff on TypingMind?

Because you install it once and use it with any model. Replica Diff 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 Replica Diff in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jakeschincariol/replica-skill/tree/main/replica-diff. 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 Replica Diff?

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 Replica Diff?

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

Is the Replica Diff AI skill free?

Yes. It is published on GitHub by Jakeschincariol 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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