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Agent skill

Niulai Style Image Transfer

by Pluviobyte in Pluviobyte/rnskill

Restyles photos, film stills or new scene descriptions in the rough low-budget 3D look observed in the 2026 animated film Niulai, with an iterative scoring loop.

Custom licenceAuto-check passedMedia & Creative

Install Niulai Style Image Transfer

skills CLI
$ npx skills add Pluviobyte/rnskill --skill rn-niulai-style-image -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Pluviobyte/rnskill rn-niulai-style-image --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/rn-niulai-style-image .claude/skills/rn-niulai-style-image && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
rn-niulai-style-image
GitHub stars
1.6k
Token cost
~1.3k tokens
SKILL.md length
502 words
Files
21 (incl. scripts, references, assets)
Skills in repo
45
Repo updated
First seen
Licence
Custom licence

At a glance

Restyles photos, film stills or new scene descriptions in the rough low-budget 3D look observed in the 2026 animated film Niulai, with an iterative scoring loop.

  • Works in 6 steps: Label the edit target as Image 1. → Select two style references from… → If a source still is wider than about… → …
  • Restyling a photo or film still in the Niulai animation look
  • SKILL.md covers Choose the mode, Prepare inputs, Build the first prompt and Iterate deliberately, plus 1 more section
  • Calls python

What it does

The skill uses the runtime's image-edit tool for an existing still and its image-generation tool only for a new scene. The default mode reproduces a rough, low-budget 3D look seen in public film frames. A separate ink-poster mode applies only when you explicitly ask for the water-ink poster look and is never mixed with the film-frame references. Results are described as matching observed public-frame visual grammar, not an official art specification.

Preparation labels the edit target as Image 1, picks two style references from the bundled assets for face and body, resizes stills wider than about 1600 px and keeps the character count, positions, action, props and camera crop. Logos, titles and watermarks are removed. The agent compares each output with the target and references using scripts/make_comparison.py, scores six rubric dimensions and iterates on one dominant failure at a time until the total reaches 27 out of 30.

When your agent uses it

  • Restyling a photo or film still in the Niulai animation look
  • Generating a new scene in that rough 3D style from a text description
  • Comparing outputs against Niulai reference frames and iterating

Example prompts

  • “Turn this street photo into a Niulai-style frame, keeping the people and the camera crop the same.”
  • “Make a new scene of a cow herd in a dark field in the Niulai film look.”
  • “Switch to the ink poster mode and restyle this portrait as the movie poster.”

Requirements

  • An image-edit or image-generation tool in your agent runtime
  • Pillow for the comparison script

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  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…
  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…

What it can do on your machine

Read from SKILL.md and the folder at commit 83d1783. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Niulai Style Image Transfer loads about 1.3k tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 98 tokens; SKILL.md has 502 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 502 words (~1,337 tokens).

“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.”

— opening of SKILL.md by Pluviobyte, Custom licence
name
rn-niulai-style-image

Read the full SKILL.md on GitHub

Files

SKILL.md and 20 other files (scripts, references, assets) in skills/rn-niulai-style-image of Pluviobyte/rnskill.

  • SKILL.md
  • agents/openai.yaml
  • assets/showcases/comparisons/chef-final-comparison.jpg
  • assets/showcases/comparisons/door-final-comparison.jpg
  • assets/showcases/comparisons/pot-final-comparison.jpg
  • assets/showcases/comparisons/service-final-comparison.jpg
  • assets/showcases/final/dragon-chef-niulai.jpg
  • assets/showcases/final/dragon-door-niulai.jpg
  • assets/showcases/final/dragon-pot-niulai.jpg
  • assets/showcases/final/dragon-service-niulai.jpg
  • assets/style-reference/niulai-calf-closeup.jpg
  • assets/style-reference/niulai-crowd-field.jpg
  • assets/style-reference/niulai-herd-dark.jpg
  • assets/style-reference/niulai-leopard-forest.jpg
  • assets/style-reference/niulai-two-cows.jpg
  • … and 6 more

Open the folder on GitHubat commit 83d1783

Compare with similar skills

Niulai Style Image Transfer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Niulai Style Image Transfer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Niulai Style Image Transfer this skillPluviobyte/rnskill1.6k—~1.3kAutomated safety check: PassCustom licence
AI Image Generation and Editingzhayujie/CowAgent47k—~1.3kAutomated safety check: PassMIT
Generate Imageynulihao/AgentSkillOS61810 repos~1.7kAutomated safety check: NotesNone
GPT Image Generation CLIwuyoscar/GPT-Image2-Skill5.7k—~2.5kAutomated safety check: NotesMIT
BlockRun Image GenerationBlockRunAI/ClawRouter6.6k—~2.1kAutomated safety check: PassMIT
Native Transparent ImagegenZSeven-W/craft-skills2251 repos~1.1kAutomated safety check: PassApache-2.0

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Categories

Questions about Niulai Style Image Transfer

What does Niulai Style Image Transfer do?

Restyles photos, film stills or new scene descriptions in the rough low-budget 3D look observed in the 2026 animated film Niulai, with an iterative scoring loop. The skill uses the runtime's image-edit tool for an existing still and its image-generation tool only for a new scene. The default mode reproduces a rough, low-budget 3D look seen in public film frames.

When should I use Niulai Style Image Transfer?

Niulai Style Image Transfer fits situations like: restyling a photo or film still in the Niulai animation look; generating a new scene in that rough 3D style from a text description; comparing outputs against Niulai reference frames and iterating.

How do I install Niulai Style Image Transfer in Claude Code?

Run `npx skills add Pluviobyte/rnskill --skill rn-niulai-style-image -a claude-code`. Or copy the skill folder (skills/rn-niulai-style-image in Pluviobyte/rnskill) into .claude/skills/rn-niulai-style-image in your project. Claude Code loads it when a task matches its description.

How do I install Niulai Style Image Transfer in Codex?

Run `npx skills add Pluviobyte/rnskill --skill rn-niulai-style-image -a codex`. Or copy the skill folder (skills/rn-niulai-style-image in Pluviobyte/rnskill) into .agents/skills/rn-niulai-style-image in your project. Codex loads it when a task matches its description.

Can I use Niulai Style Image Transfer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Pluviobyte/rnskill --skill rn-niulai-style-image -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rn-niulai-style-image, .gemini/skills/rn-niulai-style-image, .github/skills/rn-niulai-style-image and .opencode/skills/rn-niulai-style-image in your project.

What does Niulai Style Image Transfer need to run?

Going by SKILL.md and its folder, Niulai Style Image Transfer needs the command-line tools its instructions call (python). Our summary lists: An image-edit or image-generation tool in your agent runtime; Pillow for the comparison script.

Does Niulai Style Image Transfer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Niulai Style Image Transfer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Niulai Style Image Transfer use?

Niulai Style Image Transfer has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Niulai Style Image Transfer use?

About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Niulai Style Image Transfer?

Skills that share tags, products or a category with Niulai Style Image Transfer: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Generate Image (ynulihao/AgentSkillOS, 618 stars), GPT Image Generation CLI (wuyoscar/GPT-Image2-Skill, 5.7k stars) and BlockRun Image Generation (BlockRunAI/ClawRouter, 6.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Niulai Style Image Transfer?

Pluviobyte (a GitHub user) maintains it in Pluviobyte/rnskill, which has 1,639 GitHub stars. The repository holds 45 skills in this directory. The repository was last updated on September 21, 2026.

Source: Pluviobyte/rnskill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.