Agent skill

Manga Ink Explainer Visuals

by oil-oil in oil-oil/oil-visual

Makes explanatory images and transparent illustration assets in one manga-ink style with halftone screentone, in two separate output modes.

MITAuto-check passedMedia & Creative

Install Manga Ink Explainer Visuals

skills CLI
$ npx skills add oil-oil/oil-visual --skill oil-visual -a claude-code

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

GitHub CLI
$ gh skill install oil-oil/oil-visual oil-visual --agent claude-code

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

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

Facts

Skill name
oil-visual
GitHub stars
102
Token cost
~3k tokens
SKILL.md length
1,336 words
Files
18 (incl. scripts, assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Makes explanatory images and transparent illustration assets in one manga-ink style with halftone screentone, in two separate output modes.

  • Works in 9 steps: Write the visual brief → Design the labels → Build the prompt → …
  • Creating an explanatory image for a concept, workflow, comparison or tradeoff
  • SKILL.md covers Choose the output mode, Shared visual language, Mode A workflow — explanatory… and Mode B workflow — transparent…, plus 2 more sections
  • Calls python3

What it does

Oil Visual makes raster images in one shared manga-ink style: black comic outlines with varied line weight and restrained circular halftone screentone. You pick one of two output modes before generating and the modes are never mixed. Mode A is an explanatory image, a finished off-white scene delivered as a PNG or WebP with every essential title and label drawn inside the bitmap, used when the picture alone must explain a concept, mechanism, workflow, comparison or tradeoff.

Mode B is a transparent illustration meant to be placed in a hero, document, card or slide, delivered as a transparent PNG with no explanatory labels unless you ask for them. If the generator lacks native transparency, the image is drawn on a uniform chroma-key background, green by default or magenta when the subject contains green, and the bundled scripts/cutout.py removes it. Recurring subjects are optional: a minimal stick-figure person with round glasses and a chubby warm-yellow Border Collie are drawn when requested or when they help explain the point. It is not for ordinary code diagrams, photo processing or unrelated brand visuals.

When your agent uses it

  • Creating an explanatory image for a concept, workflow, comparison or tradeoff
  • Making a transparent illustration to place in a slide, card or document layout
  • Drawing the stick-figure person or the warm-yellow dog in the shared style
  • Cutting a chroma-key background out of a generated illustration

Example prompts

  • “Make an explainer image showing how a request flows through our queue, with labels drawn inside the image.”
  • “Create a transparent illustration of a laptop in the manga-ink style for my slide hero.”
  • “Draw the glasses-wearing stick figure next to the Border Collie as a reusable transparent PNG.”

Requirements

  • An image generation tool, ideally with native transparency
  • Python to run scripts/cutout.py

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Write the visual brief
  2. Design the labels
  3. Build the prompt
  4. Inspect and retry
  5. Select the subject
  6. Build the prompt
  7. Validate the source
  8. Remove a chroma-key background only
  9. Validate the transparent result

What it can do on your machine

Read from SKILL.md and the folder at commit 65ea6ac. 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:

    • python3

    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

Manga Ink Explainer Visuals loads about 3k tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 1,336 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~3k

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

The full file from oil-oil/oil-visual at commit 65ea6ac, republished under its MIT licence (© oil-oil). 1,336 words, ~3,042 tokens.

Download SKILL.mdSave it as .claude/skills/oil-visual/SKILL.md (or your agent's skills folder). This skill also uses 17 other files; get the full folder from GitHub.
name
oil-visual
description
制作统一漫画墨线风格的解释图与透明插画素材,可单独绘制眼镜线条人物、暖黄色牧羊犬、两者组合,或同风格的物件与装饰元素。当用户需要概念、机制、流程、对比的完整解释画面,或可复用的排版插图时使用;不用于普通代码图表、照片处理或无关品牌视觉。

Oil Visual

Create raster visuals in one shared manga-ink language. Choose one output mode before generating; do not mix the two production paths.

Choose the output mode

Mode A — explanatory image

Use when the image must explain a concept, mechanism, workflow, comparison, or tradeoff by itself.

  • Deliver a complete PNG or WebP with a finished off-white scene.
  • Generate every essential title and label directly inside the bitmap.
  • Make the relation visible through objects, paths, states, or repeated materials; labels identify the evidence but do not replace it.
  • Do not generate an unlabeled base and add essential words in a separate rendering step.
Mode B — transparent illustration

Use when a character, object, or decorative illustration will be composed into a hero, document, card, slide, or other layout.

  • Request a genuinely transparent PNG when the selected generator supports native alpha. Otherwise use a perfectly uniform chroma-key background that does not occur in the artwork. Default to #00FF00; use #FF00FF when the subject contains green.
  • Do not include explanatory labels unless the user explicitly requests text inside the illustration.
  • Preserve native alpha when it is clean. For a chroma-key source, remove the background with the bundled scripts/cutout.py. Deliver a transparent PNG in either case.
  • Keep the transparent artwork as a reusable visual asset; the surrounding layout supplies the title and explanatory copy.

If the destination is unclear, choose Mode A when the image itself must communicate the idea and Mode B when another layout will carry the explanation.

Shared visual language

  • Draw confident black manga/comic ink outlines with varied line weight and restrained circular halftone screentone.
  • Treat the recurring characters as optional subjects, not a required pair. When a person is selected, draw the minimal stick-figure protagonist with a round head, thin round glasses, dot eyes, a simple smile, and thin line-drawn limbs; when a dog is selected, draw the chubby warm-yellow Border Collie. Select characters only when requested or when they visibly help explain the claim; never add them merely to signal the style.
  • For object-only artwork, carry the same style through clear silhouettes, varied ink line weight, restrained circular halftone, and simple material details. Do not add a person, dog, or face to make an object feel on-brand.
  • When characters are present, keep them secondary to the subject's evidence or action unless the character itself is the requested subject.
  • Use black, white, and halftone gray as the base. Use warm yellow for the dog when present; without the dog, warm yellow may appear as a small light patch or sparse star accent, but is not required.
  • Add at most two muted semantic colors. Common mapping: blue = input/content, orange = action/warning/cost, purple = process, green = successful result.
  • Avoid 3D, glossy gradients, photorealism, wobbly sketch lines, generic card grids, dashboards, unrelated clutter, and watermarks. Deliberately requested decorative elements are valid subjects.

Mode A workflow — explanatory image

1. Write the visual brief
text
viewer_question: what should be understood in 10 seconds?
concrete_claim: one-sentence conclusion
real_objects: visible objects, interfaces, documents, tools, or states
relation: comparison, transformation, causality, sequence, hierarchy, feedback, tradeoff, or pipeline
visual_evidence: what must remain understandable when labels are ignored?
scene: believable setting and 2–4 useful environmental cues
semantic_colors: what each accent color means
labels: exact short strings plus the evidence surface for each label

Show the input, action or relation, and result. Keep one dominant focal action and no more than three major visual regions. For multiple steps, use a simple left-to-right or top-to-bottom sequence.

2. Design the labels
  • Prefer 2–6 labels. Use more only when the explanation truly needs them.
  • Keep each label short and concrete: role, action, state, or outcome.
  • Place every label on or immediately beside its evidence surface, such as a desk nameplate, task sheet, folder tab, machine, meter, lane, or result document.
  • Use modern Chinese sans-serif typography, medium or bold, large enough to read at the intended display size.
  • Do not turn body copy, commands, tables, or long paragraphs into image text. Use a deterministic layout method when dense or editable text is required.

Add this block to the generation prompt:

text
Text (verbatim): Render these exact labels as part of the bitmap illustration:
"<label 1>", "<label 2>", "<label 3>".
Use each phrase exactly once. Do not translate, paraphrase, misspell, repeat,
or add any other text. Use modern sans-serif medium/bold typography, large
and readable. Place "<label 1>" on <evidence surface>; place "<label 2>" on
<evidence surface>; place "<label 3>" on <evidence surface>.
3. Build the prompt

Use this order:

  1. State the concrete claim and shared task.
  2. Describe the real setting, selected subjects, and any action. Include the protagonist or dog only when requested or when they visibly help explain the claim.
  3. Describe the evidence objects and their geometry: aligned, nested, connected, split, transformed, repeated, or converging.
  4. Assign semantic colors.
  5. Quote the exact labels and specify each placement.
  6. Add the Mode A style anchor.
  7. End with exclusions.

Mode A style anchor:

text
Professional editorial manga/comic ink illustration. Clean confident black ink outlines with varied line weights, expressive but controlled. Use classic circular halftone screentone for gray and shadow areas. Render only the selected characters and objects; do not add a protagonist or dog automatically. Use an off-white lightly textured real environment, not a blank white canvas. Typography is modern sans-serif, medium or bold, large and readable. Color is restrained: black, white, halftone gray, warm yellow when useful, plus at most two muted semantic accent colors. No 3D, no glossy gradients, no photorealism, no generic card grid, no dashboard, no unrelated clutter, no tiny text, no long paragraphs, no watermark.
4. Inspect and retry
  1. Inspect the output at original resolution.
  2. Compare every label with the brief character by character. Confirm that each appears exactly once and that no stray text was added.
  3. Reject missing, duplicated, invented, or misspelled labels.
  4. Regenerate with one targeted correction while repeating all scene and style invariants. Do not conceal an error with a separate text layer.

Use this retry instruction:

text
Keep the scene, composition, characters, objects, colors, and all correct labels unchanged.
Change only the incorrect text "<wrong>" to the exact text "<right>".
Do not add, remove, translate, or repeat any other text.

Mode B workflow — transparent illustration asset

Show full SKILL.md (568 more words)Show less
1. Select the subject

Identify exactly which subjects are requested: the person alone, the dog alone, both together, or an object or decorative element without characters. Describe one clear action when an action is needed, and include only the props needed to establish it. For a standalone object, describe its shape, material, and distinguishing details instead. Leave generous padding around the artwork so the cutout can be composed safely.

2. Build the prompt

Describe the selected subjects first. State explicitly that no unrequested person, dog, face, or prop should appear. Then append the fixed style anchor and one background rule below.

text
Style: professional manga/comic ink illustration. Clean confident ink outlines
with varying line weights, thick for contours and thin for details, not wobbly
or sketchy. Use classic circular halftone screentone dot patterns for gray and
shadow areas. Give characters and objects the same clear silhouette and ink
language. Color usage is extremely restrained: mostly black, white, and gray
halftone; warm yellow on the dog when present, or as an optional small light
patch or sparse star accent when the dog is absent. Use no more than two muted
semantic accent colors. Render only the requested subjects.
Do not let halftone, ink, props, or the subject touch the image border. Keep
generous padding. No text, no watermark. PNG format.

Use this background rule when the generator supports genuine transparency:

text
Render on a genuinely transparent background with a clean alpha channel.
No backdrop, floor plane, cast shadow, or opaque pixels outside the artwork.

Otherwise replace <KEY_COLOR> with the selected hex color and use this rule:

text
The background must be a perfectly uniform flat <KEY_COLOR> rectangle with zero
gradient, texture, noise, speckles, shadows, floor plane, or lighting variation.
3. Validate the source
  • Inspect the image before removal.
  • For native alpha, confirm the image is RGBA, all four corners have alpha 0, and no opaque background or edge residue remains. Keep the alpha intact; do not run the cutout script.
  • For a chroma-key source, confirm all four corners are uniform and visually match the chosen key color. Reject backgrounds with gradients, texture, shadows, speckles, or artwork touching the border.
  • Preserve a chroma-key source alongside the transparent result until the output is approved.
4. Remove a chroma-key background only

Skip this step for clean native-alpha output. For a uniform chroma-key source, install Pillow if the active Python environment does not have it, then run:

bash
python3 scripts/cutout.py source.png transparent.png

Optional tuning:

bash
python3 scripts/cutout.py source.png transparent.png \
  --transparent-threshold 12 \
  --opaque-threshold 220

The script samples the image border, builds a soft alpha matte from color distance, and removes color spill from antialiased edges. It works with any uniform key color, so the key can be chosen to avoid the subject palette.

5. Validate the transparent result
  • Confirm the output is RGBA and all four corners have alpha 0.
  • Confirm every requested subject remains complete. Check glasses and thin limbs for a person, ears and tail for a dog, and narrow contours or small details for an object.
  • Check for a gray fringe at 100% zoom.
  • Confirm internal white and halftone areas were not erased.
  • Regenerate the source instead of forcing the algorithm when the background is visibly uneven.

Output handling

  • Save approved project assets inside the current project or output directory.
  • Do not leave project-referenced images only in the generator's default storage.
  • Use versioned filenames instead of overwriting an approved asset unless the user explicitly requests replacement.
  • Report the final prompt, output mode, final image path, and the transparency path used. Include the chroma-key source path and any non-default cutout options when cutout was needed.

Quality gate

For every output:

  • The subject is recognizable in about 3 seconds.
  • When the output explains something, the main action or relation is clear in about 10 seconds.
  • Only requested characters appear; when present, they serve the subject rather than becoming generic decoration.
  • Line work and halftone remain consistent; warm yellow and semantic accents follow the selected subjects and meaning.

For Mode A:

  • One claim, one focal action, and no more than three major visual regions.
  • The visual evidence still shows the relation when labels are ignored.
  • Every required label is exact, appears once, and is integrated into the correct evidence surface.
  • All labels remain readable at the intended display size.

For Mode B:

  • The output has real transparency, whether supplied natively or produced by clean background removal.
  • Thin details and internal halftone regions remain intact.
  • No source background, fringe, shadow, or border artifact remains.

© oil-oil, 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 17 other files (scripts, assets) in the repository root of oil-oil/oil-visual.

  • SKILL.md
  • .gitignore
  • LICENSE
  • README.md
  • agents/openai.yaml
  • assets/readme/hero-character.png
  • assets/readme/hero.svg
  • examples/agent-workflow-square.png
  • examples/explainer-agent-workflow.png
  • examples/explainer-cost-comparison.png
  • examples/explore-folder-spotlight.png
  • examples/feedback-loop.png
  • examples/from-complex-to-clear.png
  • examples/pipeline-bottleneck.png
  • examples/simplify-trim.png
  • examples/transparent-illustration.png
  • scripts
  • … and 1 more

Open the folder on GitHubat commit 65ea6ac

Compare with similar skills

Manga Ink Explainer Visuals 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.

Manga Ink Explainer Visuals compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Manga Ink Explainer Visuals this skilloil-oil/oil-visual102—~3kAutomated safety check: PassMIT
Md2wechatgeekjourneyx/md2wechat-skill3.7k—~3.8kAutomated safety check: PassCustom licence
Image Generationonyx-dot-app/onyx32k1 repos~1.7kAutomated safety check: PassCustom licence
SEO Image GeneratorAgriciDaniel/claude-seo19k2 repos~2.1kAutomated safety check: PassMIT
Ecom Image2buluslan/gpt-image2-ecommerce410—~2.9kAutomated safety check: PassMIT
Design Image Studiokangarooking/design-image-studio102—~1.5kAutomated safety check: PassMIT

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Questions about Manga Ink Explainer Visuals

What does Manga Ink Explainer Visuals do?

Makes explanatory images and transparent illustration assets in one manga-ink style with halftone screentone, in two separate output modes. Oil Visual makes raster images in one shared manga-ink style: black comic outlines with varied line weight and restrained circular halftone screentone. You pick one of two output modes before generating and the modes are never mixed.

When should I use Manga Ink Explainer Visuals?

Manga Ink Explainer Visuals fits situations like: creating an explanatory image for a concept, workflow, comparison or tradeoff; making a transparent illustration to place in a slide, card or document layout; drawing the stick-figure person or the warm-yellow dog in the shared style; cutting a chroma-key background out of a generated illustration.

How do I install Manga Ink Explainer Visuals in Claude Code?

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

How do I install Manga Ink Explainer Visuals in Codex?

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

Can I use Manga Ink Explainer Visuals 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 oil-oil/oil-visual --skill oil-visual -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/oil-visual, .gemini/skills/oil-visual, .github/skills/oil-visual and .opencode/skills/oil-visual in your project.

What does Manga Ink Explainer Visuals need to run?

Going by SKILL.md and its folder, Manga Ink Explainer Visuals needs the command-line tools its instructions call (python3). Our summary lists: An image generation tool, ideally with native transparency; Python to run scripts/cutout.py.

Does Manga Ink Explainer Visuals 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 Manga Ink Explainer Visuals 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 Manga Ink Explainer Visuals use?

Manga Ink Explainer Visuals is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Manga Ink Explainer Visuals use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Manga Ink Explainer Visuals?

Skills that share tags, products or a category with Manga Ink Explainer Visuals: Md2wechat (geekjourneyx/md2wechat-skill, 3.7k stars), Image Generation (onyx-dot-app/onyx, 32k stars), SEO Image Generator (AgriciDaniel/claude-seo, 19k stars) and Ecom Image2 (buluslan/gpt-image2-ecommerce, 410 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Manga Ink Explainer Visuals?

oil-oil (a GitHub user) maintains it in oil-oil/oil-visual, which has 102 GitHub stars. The repository was last updated on September 25, 2026.

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