# Oil Visual > Create a consistent oil-style visual system in two modes: finished explanatory images with short accurate labels generated directly inside the scene, and transparent character illustrations produced with a bundled background-removal script. Use for concepts, mechanisms, comparisons, workflows, tradeoffs, hero artwork, editorial character scenes, and reusable layout illustrations featuring the gla… - **Type:** Skill - **Install:** `agentstack add skill-oil-oil-oil-visual-oil-visual` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [oil-oil](https://agentstack.voostack.com/s/oil-oil) - **Installs:** 0 - **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [oil-oil](https://github.com/oil-oil) - **Source:** https://github.com/oil-oil/oil-visual ## Install ```sh agentstack add skill-oil-oil-oil-visual-oil-visual ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # 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 the character scene will be composed into a hero, document, card, slide, or other layout. - Generate the subject on 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. - Remove the background with the bundled `scripts/cutout.py` and deliver a transparent PNG. - 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. - Keep the recurring characters: a minimal stick-figure protagonist with a round head, thin round glasses, dot eyes, a simple smile, and thin line-drawn limbs; plus a chubby warm-yellow Border Collie companion. - Keep characters secondary to the subject's evidence or action. - Use black, white, and halftone gray as the base. Use warm yellow for the dog, small light patches, and sparse star accents. - 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, decorative clutter, and watermarks. ## 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: "", "", "". 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 "" on ; place "" on ; place "" on . ``` ### 3. Build the prompt Use this order: 1. State the concrete claim and shared task. 2. Describe the real setting and the protagonist/dog action. 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. Minimal cute stick-figure protagonist with round head, thin round glasses, dot eyes, simple smile, and thin line-drawn limbs. Include a chubby warm-yellow Border Collie companion. 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 for the dog, plus at most two muted semantic accent colors. No 3D, no glossy gradients, no photorealism, no generic card grid, no dashboard, no decorative 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 "" to the exact text "". Do not add, remove, translate, or repeat any other text. ``` ## Mode B workflow — transparent illustration ### 1. Describe one reusable scene Use one character action and only the objects needed to establish it. Examples: drawing at a desk, inspecting a document, holding a blueprint, or presenting a finished result. Leave generous padding around the subject so the cutout can be composed safely. ### 2. Build the prompt Describe the subject first, then append this fixed anchor: Replace `` with the selected hex color before sending the prompt. ```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. Heavy use of classic circular halftone screentone dot patterns for all gray and shadow areas. The main character is a cute minimal stick figure with a round head, thin round glasses, dot eyes, simple smile, and thin line-drawn limbs. Include a chubby warm-yellow Border Collie companion. Color usage is extremely restrained: 90% black, white, and gray halftone; warm yellow only on the dog, small light patches, and sparse star accents. The background must be a perfectly uniform flat rectangle with zero gradient, texture, noise, speckles, shadows, floor plane, or lighting variation. Do not let halftone, ink, props, or the subject touch the image border. Keep generous padding. No text, no watermark. PNG format. ``` ### 3. Validate the source - Inspect the image before removal. - 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 the source image alongside the transparent result until the output is approved. ### 4. Remove the background 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 the subject remains complete, including glasses, thin limbs, dog ears, tail, and small props. - 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, source image path when Mode B is used, final image path, and any non-default cutout options. ## Quality gate For every output: - The subject is recognizable in about 3 seconds. - The main action or relation is clear in about 10 seconds. - Characters support the subject instead of becoming generic decoration. - Line work, halftone, warm yellow, and semantic accents remain consistent. 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: - Background removal is clean and the output has real transparency. - Thin details and internal halftone regions remain intact. - No source background, fringe, shadow, or border artifact remains. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [oil-oil](https://github.com/oil-oil) - **Source:** [oil-oil/oil-visual](https://github.com/oil-oil/oil-visual) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-oil-oil-oil-visual-oil-visual - Seller: https://agentstack.voostack.com/s/oil-oil - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.