# Illustration Production > Use when the user asks to create, revise, review, prompt, art-direct, style-match, or make consistent BaseCamp illustrations and image-generation assets. Trigger for requests mentioning illustration prompts, image prompts, visual style guide, house style, style lane, taste, art direction, poster, cover art, comic panels, patient-education visuals, workshop/presentation visuals, OpenAI Image 2.0,… - **Type:** Skill - **Install:** `agentstack add skill-erafat-skills-illustration-production` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [erafat](https://agentstack.voostack.com/s/erafat) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [erafat](https://github.com/erafat) - **Source:** https://github.com/erafat/skills/tree/main/illustration-production ## Install ```sh agentstack add skill-erafat-skills-illustration-production ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Illustration Production ## Purpose Create controlled, reviewable illustration assets and image-generation prompts for BaseCamp. Core principle: > Illustration generation is not a prompt. It is a controlled visual production pipeline. ## Trigger Cues Use this skill when the user asks for any of the following: - "make an illustration", "generate an image", "create a visual", "make a cover", "make a poster", "make a comic panel" - "write an image prompt", "improve this image prompt", "prompt for OpenAI Image 2.0", "prompt for DALL-E", "prompt for Nano Banana" - "use our house style", "make it match our style", "style lane", "style guide", "taste", "art direction", "visual philosophy" - "use these images as reference", "what examples do we have", "accepted/rejected examples", "why did this output fail" - "patient education visual", "waiting room comic", "AI Beyond Chatbot illustration", "presentation visual", "AED cover" Do not use this skill for ordinary prose editing, non-visual research, deterministic UI implementation without custom illustration needs, or simple file organization unless visual taste/style/prompting is part of the task. ## Canonical Guide Read the guide first for any new or materially changed visual task: - `references/illustration-guide.md` - For a quick visual overview of what each style lane represents, read `references/style-lane-gallery.md`. Use existing project-local rules when they are more specific: - project `AGENTS.md`, `STATUS.md`, and local prompt files - established cover, comic, deck, or illustration design docs - AI Beyond Chatbot examples: `references/ai-beyond-chatbot/illustration-prompts.md` ## Intake Gate Ask a specific intake before creating or materially revising an illustration, prompt system, style lane, or visual asset. Ask 4-5 focused questions, usually: 1. Purpose and audience: what should this image do, and who is it for? 2. Asset type and destination: cover, scene card, slide visual, poster, infographic, website asset, etc.; where will it live? 3. Style lane or reference: use an existing lane/example, or create a new direction? 4. Constraints and guardrails: text policy, medical/ethical concerns, character consistency, privacy, brand limits, size/aspect ratio. 5. Autonomy level: should the agent choose and execute, or return options for sign-off first? Do not implement skill file changes without intake. For ordinary asset work, if the user explicitly says to proceed with defaults, use the guide defaults and continue. ## Style Lane Registry Current lanes: - `Warm Editorial Analog Clarity`: default house style for editorial/conceptual visuals. - `Patient Education Indie Comic`: clinic/patient education scenes, especially Waiting Room Comics. - `Minimal Academic Cover`: AED-style abstract specialist cover art. - `Swiss Editorial Clinical Flat`: clinical-academic slide illustrations and workshop visuals. - `Semantic Typography Concept Poster`: typography-led concept posters where a word or phrase becomes the image structure. - Option: `Geometric Typographic Concept Poster`, for modern flat geometric posters where the core word becomes a semantic visual symbol through type, grid, color fields, transparent layers, and minimal symbolic geometry. - Template: `references/semantic-typography-geometric-poster-template.md` - Example: `references/semantic-typography-geometric-poster-shenjingneike.md` - Example: `references/semantic-typography-epilepsy-poster-example.md` - Example: `references/semantic-typography-neurology-poster-example.md` Do not invent a new lane casually. Promote a new lane only when it has a repeated use case, accepted example, descriptor, avoid list, and a reason existing lanes do not fit. ## Workflow 1. Read the smallest relevant context. - For new work, read the canonical guide. - For project work, read the nearest `AGENTS.md` and project `STATUS.md`. - For a named lane, read that lane's canonical source. 2. Classify the task. - new asset - prompt only - style direction - iteration on existing asset - review/rejection pass - lane creation 3. Select one style lane. - Pick one lane by default. - Do not blend lanes unless the user explicitly asks or the task clearly requires it. - State the chosen lane and why it fits. 4. Choose the tool path. - Default to OpenAI Image 2.0 for visual asset production through the Codex-native image generation tool. This includes illustrations, covers, posters, visual examples, style-lane examples, and typography-led concept art. - When the user asks for Image 2.0, call the native Image 2.0 generation path directly. Do not require or check `OPENAI_API_KEY`, and do not route through CLI/API wrappers or substitute non-native generation paths. - If the native Image 2.0 tool is not exposed or callable in the current session, stop and report that exact tool-surface blocker. Do not substitute another renderer or create a lower-quality fallback unless the user explicitly authorizes that fallback after being told it is not Image 2.0. - Use Gemini / Nano Banana only when requested, when a verified project path requires it, or when OpenAI Image 2.0 is unsuitable; Gemini should run through the project-approved script/API path with credentials from environment, local untracked config, or macOS Keychain. - Do not default to deterministic HTML/SVG/PNG for illustration or poster art just because text or geometry is involved. Use deterministic code/SVG/HTML/CSS/slides only when the user explicitly asks for a deterministic/editable pathway, or when exact labels, charts, diagrams, UI, or production typography are the deliverable. 5. Label references by role. - style reference - character reference - composition reference - palette reference - mood reference - medical/device reference - negative reference 6. Draft the production prompt. - Include purpose, audience, asset type, style lane, composition, palette, text policy, constraints, and avoid list. - Use the guide's prompt architecture. - Keep important text outside generated artwork unless explicitly approved. 7. Run the pre-generation gate. - purpose clear - one lane selected - one visual idea - text policy explicit - reference roles labeled - medical/ethical guardrails explicit when relevant - output unit appropriate for the model 8. Generate, draw, or hand off. - For raster image generation, use the Codex-native OpenAI Image 2.0 generation path and save accepted outputs into the project workspace. - Never answer an Image 2.0 request with a non-native substitute. - If native Image 2.0 generation is unavailable, hand off with the final prompt set, reference roles, and blocker instead of silently downgrading. - For prompt-only tasks, deliver the prompt plus review checklist. - For deterministic visuals explicitly requested by the user, build the visual in code or the appropriate document/presentation tool. 9. Review the output. - Check purpose fit, lane consistency, composition, palette, character consistency, bias/authority drift, text policy, medical plausibility, and thumbnail/distance readability. - Save accepted project-bound assets in the workspace or project folder, not only in a temporary/generated location. - Log rejected examples with a one-line failure mode when useful. ## Iteration Path For an existing asset, do not restart from scratch by default. 1. Identify the accepted lane and source prompt. 2. Name the exact failure: composition, palette, character drift, text, medical cue, density, or tone. 3. Make one targeted change. 4. Re-run the review gate. ## Output Contract When producing prompts or assets, report: - selected style lane - model/tool path - reference roles used - final prompt or prompt delta - review checklist result - saved asset paths, if any Keep the response concise unless the user asks for a full art-direction packet. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [erafat](https://github.com/erafat) - **Source:** [erafat/skills](https://github.com/erafat/skills) - **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-erafat-skills-illustration-production - Seller: https://agentstack.voostack.com/s/erafat - 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%.