Agent skill

Extract Visual Style 2

by ajinnaaa in ajinnaaa/extract-visual-style-2

Extract, reverse-engineer, and codify transferable visual-style systems from images, animation, illustration, live-action film, television, commercials, or video.

MITAuto-check passedMedia & Creative

Install Extract Visual Style 2

skills CLI
$ npx skills add ajinnaaa/extract-visual-style-2 --skill extract-visual-style-2 -a claude-code

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

GitHub CLI
$ gh skill install ajinnaaa/extract-visual-style-2 extract-visual-style-2 --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/ajinnaaa/extract-visual-style-2.git skills-src && mkdir -p .claude/skills && cp -r skills-src/extract-visual-style-2 .claude/skills/extract-visual-style-2 && 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
extract-visual-style-2
GitHub stars
124
Token cost
~2.3k tokens
SKILL.md length
1,073 words
Files
6 (incl. references)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Extract, reverse-engineer, and codify transferable visual-style systems from images, animation, illustration, live-action film, television, commercials, or video.

  • Works in 4 steps: Always read references/output-contract.md. → Classify the source and read the… → Select one operating mode → …
  • The user explicitly invokes 风格提取2
  • SKILL.md covers Purpose, Route the task, Audit the evidence and Separate four kinds of…, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Extract Visual Style 2 is an agent skill from ajinnaaa/extract-visual-style-2. Extract, reverse-engineer, and codify transferable visual-style systems from images, animation, illustration, live-action film, television, commercials, or video. Use when the user explicitly invokes 风格提取2 or $extract-visual-style-2, or asks for 项目美术风格规范、视觉圣经、AI生图规范、系列视觉一致性、团队级色彩/灯光/空间/材质系统, a project art-direction bible, or project-level calibration of generated results. Supports quick extraction when explicitly invoked, full transferable analysis, and project-style-bible outputs. Default to analysis and prompt…

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `agents/openai.yaml`, `references/animation.md` and `references/film.md`).

It sits in Media & Creative, covering Image generation and Performance reviews. The repository describes itself as: 从参考素材提取项目级视觉系统、视觉圣经与提示词的 Codex Skill. The licence is MIT.

When your agent uses it

  • The user explicitly invokes 风格提取2
  • $extract-visual-style-2
  • Asks for 项目美术风格规范、视觉圣经、AI生图规范、系列视觉一致性、团队级色彩/灯光/空间/材质系统
  • A project art-direction bible

Example prompts

  • “/extract-visual-style-2”

Workflow steps

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

  1. Always read references/output-contract.md.
  2. Classify the source and read the matching medium reference
  3. Select one operating mode
  4. Honor the requested scope. Explicit exclusions such as no concrete content, no aspect ratio, no artist names, no prompts, analysis only…

What it can do on your machine

Read from SKILL.md and the folder at commit 7b7d2c2. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Extract Visual Style 2 loads about 2.3k tokens when it runs, and up to ~9.1k if it reads all its reference files. Until then it costs about 159 tokens; SKILL.md has 1,073 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~159
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.1k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from ajinnaaa/extract-visual-style-2 at commit 7b7d2c2, republished under its MIT licence (© ajinnaaa). 1,073 words, ~2,277 tokens.

Download SKILL.mdSave it as .claude/skills/extract-visual-style-2/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
extract-visual-style-2
description
Extract, reverse-engineer, and codify transferable visual-style systems from images, animation, illustration, live-action film, television, commercials, or video. Use when the user explicitly invokes 风格提取2 or $extract-visual-style-2, or asks for 项目美术风格规范、视觉圣经、AI生图规范、系列视觉一致性、团队级色彩/灯光/空间/材质系统, a project art-direction bible, or project-level calibration of generated results. Supports quick extraction when explicitly invoked, full transferable analysis, and project-style-bible outputs. Default to analysis and prompt delivery only; do not generate images or videos unless explicitly requested in the same request.

Extract Visual Style 2

Purpose

Turn visual evidence into a reusable, production-ready visual system. Explain how the images work, not merely what they contain. Preserve evidence discipline, content/style separation, character/background/coexistence controls, and prompt modules, then extend them into project-level color, lighting, space, composition, material, effects, compositing, and acceptance systems.

Do not generate images or videos unless the user explicitly requests generation in the same request.

Route the task

  1. Always read references/output-contract.md.
  2. Classify the source and read the matching medium reference:
    • animation, anime, illustration, motion comic, painted animation, or stylized CG: read references/animation.md
    • live-action film, television, commercial, documentary, music video, or photographic AI-video target: read references/film.md
    • hybrid work: read both
  3. Select one operating mode:
    • Quick extraction: concise style identity, stable core, important conditionals, and requested prompt.
    • Full transferable system: complete character, background, coexistence, film/motion, prompt, evidence, and confidence structure.
    • Project style bible: when the user asks for a visual bible, art-direction guide, project style specification, series consistency system, or team generation standard, also read references/project-style-bible.md.
    • Calibration: when generated results are supplied, diagnose and replace faulty rules instead of accumulating negatives.
  4. Honor the requested scope. Explicit exclusions such as no concrete content, no aspect ratio, no artist names, no prompts, analysis only, or background only are hard limits.

Audit the evidence

Inspect every supplied image or usable frame before drafting. For video, sample materially different moments when tools permit. If only stills, posters, trailers, publicity images, or secondary sources are available, state that limit next to the affected conclusion.

Use these adequacy labels:

  • one sample: provisional single-sample style
  • two to five varied samples: tentative shared style
  • six or more varied samples covering different subjects, environments, lighting conditions, and shot sizes: stronger series-level evidence

For each important rule, record:

  • visible evidence
  • sample coverage
  • stable, conditional, or scene-specific status
  • observed, inferred, proposed, or unknown status
  • confidence: high, medium, or low

Never infer a specific camera, lens model, sensor, stock, LUT, software, or production method from appearance alone. Verify production facts or describe only the visible effect.

Separate four kinds of information

Privately classify source information before writing:

  1. Content: identities, objects, locations, actions, story events, costume specifics, logos, and text.
  2. Transferable style: shape grammar, edge behavior, color roles, lighting logic, texture, space, composition, motion, and finishing.
  3. Production locks: user-approved aspect ratio, delivery size, medium, compositing purpose, continuity requirements, or model constraints.
  4. Scene locks: content or geometry required only for a particular scene or shot.

Keep scene locks out of the global style core. Keep production locks visible in project specifications, but omit them from content-free prompts when the user excludes them.

Build the style architecture

Organize every rule into three layers:

  1. Stable core: repeated across most suitable samples and safe across the project.
  2. Conditional variants: changes with character identity, location, time, weather, shot size, emotional function, or narrative emphasis.
  3. Scene-specific locks: required only for one scene or shot and never presented as universal style.

Do not average away meaningful differences. A coherent project does not require identical brightness, palette, texture density, or motion in every scene; it requires consistent governing logic.

Map the visual systems

Analyze only relevant systems, but keep their responsibilities distinct:

  • Project identity: the few invariants whose loss would make the work feel like a different project.
  • Rendering and shape: medium, construction, silhouette, line, edge, anatomy, and abstraction.
  • Color: base environment, local/material color, accents, complexion, value, and saturation hierarchy.
  • Lighting: source, direction, quality, exposure, shadow, practical motivation, atmosphere, and subject landing zone.
  • Space: depth layers, scale references, perspective, occlusion, reveal, path, enclosure, and navigability.
  • Composition and lens: shot-size tendency, camera height, focal tendency, negative space, symmetry, framing, and focal placement.
  • Material: surface structure, roughness, reflectance, wear, age, moisture, translucency, and prohibited substitutions.
  • Character: proportion, face, identity variation, hair, clothing, local color, and texture.
  • Background: geometry, grouping, detail density, palette, atmosphere, depth, and environmental motion.
  • Coexistence and compositing: shared light, color temperature, grain, sharpness, overlap, scale, subject zone, and clean-plate usability.
  • Effects physics: source, attachment, propagation path, intensity, falloff, environmental response, and temporal behavior.
  • Motion and time: subject motion, camera motion, cadence, acceleration, settling, focus, blur, texture stability, and cutting rhythm.

For each rule, name the owning system. Do not let color perform the job of anatomical structure, fog perform the job of depth everywhere, grading replace production design, or effects lighting ignore the surrounding material response.

Show full SKILL.md (348 more words)Show less

Write operational rules

Replace vague labels with controllable instructions. A useful rule specifies:

  • location or owner
  • direction or behavior
  • relative strength
  • visual purpose
  • condition or exception
  • failure mode when useful

Prefer relationships over unsupported numerical precision. Use ratios, percentages, hex values, focal lengths, or thresholds only when supplied, measured, repeatedly supported, or clearly labeled as proposed production guidance.

Compile prompts

Keep reusable style separate from scene content. Use modular blocks when prompts are requested:

  1. global style core
  2. color system
  3. lighting system or conditional lighting preset
  4. space, composition, and lens system
  5. material system
  6. character-only system
  7. background-only system
  8. coexistence and compositing system
  9. effects physics when relevant
  10. video motion and temporal system when relevant
  11. negative constraints tied to demonstrated or plausible failure modes
  12. optional production and scene locks

For a content-free prompt, begin with 【在这里填写人物或场景内容】 and remove sample-specific nouns. When the user asks for a complete prompt, provide a fully merged copy-ready version after the modules.

Calibrate generated results

When results are returned:

  1. identify the visible mismatch
  2. assign it to the owning visual system
  3. find the ambiguous, missing, or conflicting instruction
  4. replace the cause with a rule specifying location, strength, behavior, and exception
  5. classify the replacement as stable core, conditional variant, production lock, or scene lock
  6. remove obsolete negatives or rules
  7. reissue the affected module and a merged prompt when requested

Do not call an untested prompt a validated project standard.

Final checks

Before delivery, verify:

  • evidence limits are stated without overwhelming the answer
  • content, transferable style, production locks, and scene locks are separated
  • stable rules and conditional variants are not mixed
  • project identity is expressed as operational invariants, not genre labels
  • color, lighting, space, composition, material, effects, and motion do not contradict one another
  • character, background, and coexistence are separated when relevant
  • technical production facts are verified or marked unknown
  • quantitative values are supported or labeled proposed
  • negative constraints target failure modes rather than becoming a generic blacklist
  • project-bible outputs include an actionable acceptance method
  • no generation occurred unless explicitly requested

© ajinnaaa, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in extract-visual-style-2 of ajinnaaa/extract-visual-style-2.

  • SKILL.md
  • agents/openai.yaml
  • references/animation.md
  • references/film.md
  • references/output-contract.md
  • references/project-style-bible.md

Open the folder on GitHubat commit 7b7d2c2

Compare with similar skills

Extract Visual Style 2 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.

Extract Visual Style 2 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Extract Visual Style 2 this skillajinnaaa/extract-visual-style-2124—~2.3kAutomated safety check: PassMIT
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Profile Optimizercharlie947/social-media-skills3.8k—~2.9kAutomated safety check: PassMIT
Make FiguresAperivue/medsci-skills331—~8.4kAutomated safety check: PassMIT
AI Image Generation and Editingzhayujie/CowAgent47k—~1.3kAutomated safety check: PassMIT

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Questions about Extract Visual Style 2

What does Extract Visual Style 2 do?

Extract, reverse-engineer, and codify transferable visual-style systems from images, animation, illustration, live-action film, television, commercials, or video. Extract Visual Style 2 is an agent skill from ajinnaaa/extract-visual-style-2. Extract, reverse-engineer, and codify transferable visual-style systems from images, animation, illustration, live-action film, television, commercials, or video.

When should I use Extract Visual Style 2?

Extract Visual Style 2 fits situations like: the user explicitly invokes 风格提取2; $extract-visual-style-2; asks for 项目美术风格规范、视觉圣经、AI生图规范、系列视觉一致性、团队级色彩/灯光/空间/材质系统; A project art-direction bible.

How do I install Extract Visual Style 2 in Claude Code?

Run `npx skills add ajinnaaa/extract-visual-style-2 --skill extract-visual-style-2 -a claude-code`. Or copy the skill folder (extract-visual-style-2 in ajinnaaa/extract-visual-style-2) into .claude/skills/extract-visual-style-2 in your project. Claude Code loads it when a task matches its description.

How do I install Extract Visual Style 2 in Codex?

Run `npx skills add ajinnaaa/extract-visual-style-2 --skill extract-visual-style-2 -a codex`. Or copy the skill folder (extract-visual-style-2 in ajinnaaa/extract-visual-style-2) into .agents/skills/extract-visual-style-2 in your project. Codex loads it when a task matches its description.

Can I use Extract Visual Style 2 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 ajinnaaa/extract-visual-style-2 --skill extract-visual-style-2 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/extract-visual-style-2, .gemini/skills/extract-visual-style-2, .github/skills/extract-visual-style-2 and .opencode/skills/extract-visual-style-2 in your project.

What does Extract Visual Style 2 need to run?

SKILL.md names no scripts, command-line tools or credentials: Extract Visual Style 2 is instructions for the agent only.

Does Extract Visual Style 2 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 Extract Visual Style 2 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. Review the folder before installing.

What licence does Extract Visual Style 2 use?

Extract Visual Style 2 is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Extract Visual Style 2 use?

About 2.3k tokens (SKILL.md is roughly 9.1k 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 6.8k tokens, read only when the agent opens those files.

What are the alternatives to Extract Visual Style 2?

Skills that share tags, products or a category with Extract Visual Style 2: Run SEO Page Loop (tsingyuai/growth-lab, 2k stars), AI Chart Image Generator (SpaceZephyr/design-buddy, 175 stars), Profile Optimizer (charlie947/social-media-skills, 3.8k stars) and Make Figures (Aperivue/medsci-skills, 331 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Extract Visual Style 2?

ajinnaaa (a GitHub user) maintains it in ajinnaaa/extract-visual-style-2, which has 124 GitHub stars. The repository was last updated on August 23, 2026.

Source: ajinnaaa/extract-visual-style-2 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.