Rn Niulai Style Image logo

Rn Niulai Style Image

CommunityPopular
Pluviobyte
rn-niulai-style-image

Transform photos, film stills, or new scene descriptions into the observed visual grammar of the 2026 animated film 《牛来》. Use when the user asks for 牛来风格、牛来正片风格、粗粝低模动物 3D、把真人画面改成牛来式动画,or requests iterative comparison against 《牛来》 references. Default to the rough film-3D mode; use the separate ink-poster mode only when the user explicitly asks for the movie poster look.

Overview

PublisherPluviobyte
Repositoryrnskill
Skill namern-niulai-style-image
Stars
1.6K
Forks
181
Bundled files
18
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 Pluviobyte on GitHub. Read the source before you install it.

Installation

Install the Rn Niulai Style Image 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/Pluviobyte/rnskill.git /tmp/rnskill
mkdir -p .claude/skills
cp -r /tmp/rnskill/skills/rn-niulai-style-image .claude/skills/rn-niulai-style-image
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rn Niulai Style Image 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 Rn Niulai Style Image 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 Rn Niulai Style Image 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.

牛来风格图片生成

Use the runtime's image-edit tool for an existing still and its image-generation tool only for a new scene. Treat the task as style-transfer when an edit target exists and as stylized-concept for a new scene.

Choose the mode

  • Default to niulai-film-3d: rough low-budget 3D observed in public film frames.
  • Use niulai-poster-ink only when the user explicitly asks for the water-ink poster. Never mix the poster with the film-frame references.
  • Describe the result as matching the observed public-frame visual grammar, not as an official art specification.

Read style-spec.md before authoring the prompt. Read evaluation-rubric.md before judging any output.

Prepare inputs

  1. Label the edit target as Image 1.
  2. Select two style references from assets/style-reference/ that cover face and body. The image tool accepts at most three inputs total.
  3. If a source still is wider than about 1600 px, resize a working copy first. Oversized stills fail.
  4. Preserve the target's character count, positions, action, clothing-color roles, key props, and camera crop unless the user asks to change them.
  5. Remove source logos, titles, dates, subtitles, and watermarks from the output.
  6. If a still is blocked by moderation, stop that still and switch to another adult scene. Do not paraphrase to retry. Prefer stills of adults; skip group shots of children.

Build the first prompt

Use this structure:

text
Use case: style-transfer
Asset type: <intended use and aspect>
Input images: Image 1 is the edit target; Images 2-N are style references. Match the look of Images 2-N, not a polished 3D reinterpretation.
Primary request: Rebuild Image 1 as cheap inflatable-costume 3D from an early-2000s amateur animation, while preserving <scene invariants>.
Character translation: Replace people with distinct upright bovine characters whose bodies are sausage-like inflatable suits; preserve identity through role, clothing color, pose, and left-right position rather than human facial likeness.
Style/medium: balloon torsos with almost no waist; oversized mask heads; pale plastic muzzles; small half-lidded eyes; uneven blunt horns; short tube limbs; mitten hands; white sock-hooves; blurry low-resolution fur-color bitmaps stretched across smooth blobby meshes; broad smears, visible seams and scale mismatch; weak contact shadows; primitive flat lighting; stock tutorial trees and painted backdrops; mild cinema-screen capture softness.
Constraints: <invariants>; no text, logo, watermark, subtitle, or date.
Avoid: professional 3D, clean low-poly, cinematic game art, realistic fur, appealing mascot design, Pixar/Disney, global illumination, correct human anatomy under an animal head.

Do not ask merely for "low poly." That usually produces clean modern game art and misses the target. The dominant miss is a well-made animal-headed human. If the body has a waist, articulated fingers, groomed fur, or cinematic light, the result is wrong.

Iterate deliberately

  1. Generate one first-pass image.
  2. Compare target, style reference, and output with scripts/.venv/bin/python scripts/make_comparison.py when local paths are available. Create scripts/.venv and install Pillow if that interpreter is missing.
  3. Score all six rubric dimensions. Continue if total score is below 27/30, any dimension is below 4, or an automatic-fail condition applies.
  4. Change one dominant failure per iteration:
    • live-action leftover -> rebuild the whole frame as 3D, including walls, props, and fire;
    • too polished -> degrade texture scale, seams, lighting coherence, and capture sharpness;
    • too cute -> flatten expressions, shrink eyes, widen muzzle, stiffen pose;
    • mascot-in-a-photo or vinyl suit -> replace with balloon geometry and blurry stretched low-resolution color bitmaps;
    • ragdoll overshoot -> remove button eyes, Frankenstein stitches, and letter prints;
    • reference bleed -> do not use a leopard/print ref unless the target character is spotted;
    • generic low-poly -> replace crisp facets with blobby forms and mismatched pasted textures;
    • material still looks skilled -> remove embossed/procedural detail, flatten to blurry low-resolution bitmaps, broad UV smears, and simple smooth meshes;
    • scene drift -> repeat character count, positions, props, and action invariants;
    • character merging -> name every character by position and action.
  5. Re-state all invariants on every edit. Stop only after the threshold passes.

Keep iteration history under assets/showcases/iterations/ when building or validating this Skill. Save selected finals under assets/showcases/final/.

Deliver

Report:

  • final image paths;
  • final prompt or prompt template;
  • per-image rubric score;
  • which iteration changed the result materially;
  • built-in image generation as the execution mode.

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 Rn Niulai Style Image AI skill do?

Transform photos, film stills, or new scene descriptions into the observed visual grammar of the 2026 animated film 《牛来》. Use when the user asks for 牛来风格、牛来正片风格、粗粝低模动物 3D、把真人画面改成牛来式动画,or requests iterative comparison against 《牛来》 references. Default to the rough film-3D mode; use the separate ink-poster mode only when the user explicitly asks for the movie poster look.

Why use Rn Niulai Style Image on TypingMind?

Because you install it once and use it with any model. Rn Niulai Style Image 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 Rn Niulai Style Image in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Pluviobyte/rnskill/tree/main/skills/rn-niulai-style-image. 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 Rn Niulai Style Image?

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 Rn Niulai Style Image?

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

Is the Rn Niulai Style Image AI skill free?

It is published on GitHub by Pluviobyte. Check the repository for licensing terms. 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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