/xhs-imagen

name: xhs-imagen
description: Create complete Xiaohongshu image-and-text posts from a topic, article, document, or rough idea, including research, fact checking, post copy, pagination, storyboards, a 3:4 cover, 9:16 content pages, image generation or fully local SVG-to-PNG fallback, and final quality review. Use for 小红书图文、小红书封面、知识卡片、漫画科普、文章转图片、AI/科技科普图组、逐页生图提示词, or revisions to an existing Xiaohongshu series. Prefer an available image-generation model; use the bundled local renderer only when no image-generation tool is available. Apply an SVG text patch only after the user explicitly reports incorrect or unreadable text in an image.

xhs-imagen

Turn one topic or source article into a publication-ready Xiaohongshu post package.

Required result

Create:

output/<topic-slug>/
├── project.json
├── research.md
├── post.md
├── storyboard.md
├── prompts/
│   ├── 00-cover.md
│   ├── 01-*.md
│   └── ...
├── images/
│   ├── cover.png
│   ├── page-01.png
│   └── ...
└── qa-report.md

If the user requests only part of the package, create only that part. Never claim that images were generated when no image-generation or local SVG renderer was available.

Fixed Xiaohongshu defaults

• Create a `3:4` cover, recommended `1080 × 1440`.
• Create `9:16` information pages, recommended `1080 × 1920`.
• Default to one cover plus 5–8 information pages.
• Use Simplified Chinese unless requested otherwise.
• Explain one dominant idea per page.
• Optimize titles and labels for phone reading.
• Do not render page numbers or page-position markers such as `04`, `01/08`, or `PAGE 04`. Keep ordering only in filenames. Numbered steps are allowed when the numbers explain the content itself.
• Default to the `alpaca-line-art` profile: pure-white background, fine black hand-drawn lines, and the bundled white alpaca creator IP.
• Preserve `glasses-chibi-blue` as a selectable profile for the original glasses-wearing host, warm off-white paper, and cobalt-blue comic style.
• Use `toolbox-bot-risograph` for tool ecosystems, plugins, Skills, Agents, and workflows in two-color risograph.
• Use `maker-girl-editorial` for professional AI Coding, workplace, tutorial, and opinion content in modern editorial illustration.
• Use `cyber-luban-woodcut` for Skill–Harness–Agent architecture and system-building topics in new-Chinese woodcut.
• Use `capybara-gouache` for beginner explainers, pitfalls, reassurance, and everyday analogies in warm gouache.
• Make the character perform the page's core conceptual action; never use it as corner decoration.

Read [references/visual-profiles.md](references/visual-profiles.md), [references/visual-style.md](references/visual-style.md), and [references/character-consistency.md](references/character-consistency.md) before producing images.

Workflow

1. Resolve the brief

Determine or infer:

• topic, audience, and desired outcome;
• the single sentence readers should remember;
• source material and whether facts may have changed;
• page count and language;
• selected visual profile, character, palette, and brand constraints;
• whether the user wants a complete package, images, copy, or prompts.

Use beginner-friendly AI/technology education as the default audience and tone when the request does not specify them.

Store the choice in `project.json` as `visual_profile`. Honor an explicit user choice; otherwise use the default declared in `references/visual-profiles.json`. Use one profile for the whole series unless the user explicitly requests otherwise.

When reviewing pages the user selected or rejected, distinguish explicit feedback from inferred preference. Treat only explicitly confirmed rules as durable defaults; use the final selection primarily to understand visual appeal and expression accuracy rather than infer rigid layout rules.

2. Research before writing

Search primary and authoritative sources for current, technical, disputed, product-specific, numerical, legal, or attributed claims. Write a claim table to `research.md`. Separate sourced facts from analogies and editorial framing.

Read [references/fact-checking.md](references/fact-checking.md) for detailed rules.

3. Build the content arc

Create:

• one thesis;
• one useful analogy;
• one misconception;
• 4–7 supporting ideas;
• one limitation, boundary, or human-control point;
• one final takeaway.

Select pages by cognitive anchors instead of distributing content evenly. Keep only moments that change what the reader understands: a core judgment, cognitive turn, comparison, bottleneck, boundary, common mistake, state change, or takeaway. Drop a page when removing it does not weaken the learning arc.

For every selected page:

1. state the cognitive anchor and why it deserves a page; 2. convert the abstract concept into a physical action; 3. map that action to one ordinary low-tech object; 4. make the character perform the action so the metaphor depends on the character.

Write `post.md` with a Xiaohongshu title, publishable body copy, optional source note, and relevant hashtags. Write `storyboard.md` before generating images.

Read [references/content-planning.md](references/content-planning.md) when choosing pages and reducing copy. Read [references/visual-metaphors.md](references/visual-metaphors.md) before writing the storyboard or image prompts.

4. Create and validate the project

Store exact content and page decisions in `project.json`. Start from [references/project.template.json](references/project.template.json) and follow [references/project.schema.json](references/project.schema.json).

Validate it:

python3 scripts/validate_project.py /absolute/path/project.json

Generate the image-model prompt files:

python3 scripts/make_prompt_pack.py \
  /absolute/path/project.json \
  --output-dir /absolute/path/output/prompts

5. Choose the rendering path automatically

When an image-generation tool is available

Use it as the default path.

1. Resolv