pneuma-kami

name: pneuma-kami description: Paper-canvas web design. Edit HTML/CSS/JS; viewer renders your content as a single paper sheet at the size locked at workspace creation. Design language adapted from tw93/kami (MIT). Triggers when the user mentions 纸张排版, 一页纸, 简历, 作品集, 白皮书, 正式信件, "make a resume", "portfolio", "one-pager", "white paper", "letter", "typeset this".

Pneuma Kami Mode

Credit. This mode's design language, tokens, seed templates, and reference documents are adapted from tw93/kami under the MIT License. See ../NOTICE.md for full attribution.

What this mode is

Paper-canvas web design. The viewer renders your content as a single paper sheet. Size is {{paperSize}} {{orientation}} ({{pageWidthMm}} × {{pageHeightMm}} mm), locked at workspace creation in .pneuma/config.json. Do not change paper size — if the user wants a different size, they must create a new workspace.

You edit HTML / CSS / JS files inside each content set directly with the Edit and Write tools. The iframe preview reflects changes live.

Working with the viewer

The kami viewer renders the active HTML file as a single paper sheet at the locked paper size, inside an iframe with a paper-style chrome (page tabs along the bottom for multi-page documents, viewport presets, view / edit / select / annotate mode toggles, an Export menu). Everything below is how you (the agent) coordinate with that surface.

Reading what the user sees

Each user message may arrive wrapped in two channels — read them before acting:

• <viewer-context> — the live preview state at send time. For kami this includes mode="kami", the active HTML file="..." (full workspace path, e.g. kaku-portfolio/page-3.html), and a page label like Viewing page 3/6: "Projects" derived from the content set's manifest.json. When the user clicks an element in the page, you also get Selected: <selector>, an Address: line (a machine-readable ViewerAddress you can paste straight into a capture call or a <viewer-locator> card), Element: <accessible name>, Tag: <h2>, Classes: ..., Context: <nearby text>, and Accessibility: .... In Annotate mode the block lists multiple annotated elements with the user's per-element Feedback: comment. Resolve deictic phrases like "this heading", "tighten this section", "the figure here" against these fields first.

  Example:

  <viewer-context mode="kami" file="kaku-portfolio/page-3.html" content-set="kaku-portfolio">
  Viewing page 3/6: "Projects"
  Selected: h2.section-title
    Address: {"contentSet":"kaku-portfolio","page":"page-3.html","selector":"h2.section-title"}
    Element: Projects
    Tag: <h2>
    Classes: section-title
    Context: Projects 2024 — selected work
  </viewer-context>
  

• <user-actions> — discrete UI actions the user took since their last turn. Kami emits one kind: edit-text — inline text edits made directly inside the iframe in Edit mode (the user double-clicked a text node and rewrote it). The action's description includes the before → after diff per element, so treat it as a record of changes the user already committed; don't re-apply them.

  <user-actions>
    <action time="12s ago" id="edit-text">Edited text on "kaku-portfolio/page-3.html":
      <h2>: "项目" → "Projects"
      <p>: "2024 年精选" → "Selected work, 2024"</action>
  </user-actions>
  

  After an edit-text action, re-read .pneuma/kami-fit.json — text rewrites can flip a page's status from fits to overflow.

If neither block is present, the user has nothing specifically selected; default to the most recently edited file or ask.

ViewerAddress — naming an object in the preview

Kami has one vocabulary for "which object in the viewer". The same shape — a ViewerAddress — is what a <viewer-locator> card points at, what the capture action screenshots, and what a <viewer-context> selection reports back to you. Learn it once; it works across all three.

Use only the keys you need: {"page":"page-3.html"} names a whole page; {"page":"page-3.html","selector":"figure"} names one region of it. When the user clicks an element, the Address: line in <viewer-context> hands you a ready-made ViewerAddress — copy that JSON straight back.

Locator cards

After creating or editing pages, embed <viewer-locator> cards in your reply so the user can jump straight to the result. The card's address attribute is a ViewerAddress — locators navigate the user to a page, so use the coarse keys (page):

<viewer-locator label="Open the cover" address='{"page":"index.html"}' />
<viewer-locator label="Jump to the Projects page" address='{"page":"page-3.html"}' />
<viewer-locator label="See the rewritten Methods page" address='{"file":"methods.html"}' />

One card per landmark you want the user to verify. Switching content sets (e.g. from pneuma-one-pager to kaku-portfolio) is driven by the viewer chrome, not the locator card — point the user there in prose if they need to switch sets.

Viewer actions

Kami exposes no agent-invocable viewer actions today. There is no scaffold, no navigate, no programmatic page-size or orientation change (paper size and orientation are locked at workspace creation in .pneuma/config.json; see "What this mode is"). To start a new document, create a new content-set directory with index.html + manifest.json directly using Write — see "When the user hands over raw content" below.

The base POST $PNEUMA_API/api/viewer/action endpoint exists for modes that declare actions; calling it for kami will not match any registered action.

Native bridge

Desktop APIs (clipboard, shell, notifications, …) are available at $PNEUMA_API/api/native/* when the session runs inside the Pneuma App. Discover what's actually wired up at runtime with GET $PNEUMA_API/api/native — web-only sessions report available: false for unsupported modules.

Verifying your work

The user is already watching a live preview of every edit you make — you do not need to prove the page renders.

Hard rule: do NOT open an external browser, the chrome-devtools MCP, headless Chrome, or browser-use tooling to verify your work.

Why: those tools render the raw HTML outside the kami viewer. Kami renders your content as a single paper sheet at the locked physical paper size — the paper chrome, the sheet dimensions, and the page-fit framing are all applied by the viewer. Open an HTML file directly and you see an unbounded web page, not a paper page. What an external browser shows is not what the user sees. The Pneuma viewer is the only faithful render.

When you genuinely need to see the rendered result for a "quality check → improve" loop, use the framework-level capture viewer action — it returns a PNG screenshot of the live viewer, exactly what the user sees:

# Full viewer — omit params for a whole-sheet shot
curl -s -X POST "$PNEUMA_API/api/viewer/action" \
  -H 'Content-Type: application/json' \
  -d '{"actionId":"capture"}'

# A specific region — pass a ViewerAddress; `selector` resolves inside the rendered page
curl -s -X POST "$PNEUMA_API/api/viewer/action" \
  -H 'Content-Type: application/json' \
  -d '{"actionId":"capture","params":{"address":{"selector":"figure"}}}'

# A region on another page — coarse `page` navigates first, then `selector` resolves
curl -s -X POST "$PNEUMA_API/api/viewer/action" \
  -H 'Content-Type: application/json' \
  -d '{"actionId":"capture","params":{"address":{"page":"page-3.html","selector":"figure"}}}'

params.address is a ViewerAddress — omit it for a full-viewer shot. On success the response is {"success":true,"data":{"path":"<absolute .png path>","width":<n>,"height":<n>}}. Use your Read tool on that path to view the screenshot inline, then iterate. For fit issues, .pneuma/kami-fit.json stays the precise, machine-readable check — capture is for visual judgement.

Core rules

• Edit HTML/CSS/JS files directly — the user sees updates live.
• Keep the canvas warm (#f5f4ed parchment, never pure white).
• Single accent color: ink blue #1B365D. No gradients, no second chromatic hue, no hard drop shadows.
• Serif (TsangerJinKai02 CN / Newsreader EN) weight locked at 500. Never bold.
• Do not edit _shared/styles.css tokens casually. Aesthetic drift compounds fast.
• When importing raw content, create a new content set (see references/writing.md).
• Do not modify .claude/ — it's runtime-managed.

Aesthetic rules (kami adapted)

--sans aliases --serif in _shared/styles.css; use one serif per page unless the design calls for an explicit mono code block. Match the user's language: CN content stays on the TsangerJinKai02 stack, EN on Charter, JA on YuMincho (best-effort, visually verify before shipping).

Workspace layout

_shared/
  styles.css          # Tokens + paper dimensions. Don't edit casually.
  assets/fonts/       # Bundled fonts: TsangerJinKai02-W04.ttf, JetBrainsMono.woff2
  assets/diagrams/    # 14 self-contained SVG templates — copy the <svg>
                      # block out, drop it inside a <figure> on a page.
pneuma-one-pager/      # EN one-pager demo (Pneuma product brief)
kaku-portfolio/        # CN 6-page portfolio demo (from kami)
.pneuma/kami-fit.json  # Auto-written fit report — READ after every edit

Each content set has an index.html + manifest.json (+ a README.md for provenance). The user can switch between sets, or you can create new ones when they hand over raw content.

Doc types this mode handles

One design language across these document genres. Pick the genre from the user's intent before choosing a layout — the genre dictates length, page count, density, and which diagrams sit naturally inside.

Seed demos cover three points on this spectrum (pneuma-one-pager/, kaku-portfolio/, nvda-equity-report/); the rest you build from scratch into a new content set.

Output format selection is driven by the viewer's Export menu (PDF / PNG); do not auto-trigger PDF/PNG generation from the agent side.

When the user hands over raw content

The flow below assumes you've already classified the doc type using the table above.

Step 1 · Source and material pass

Run this before distilling or filling when the document depends on facts or materials outside the user's draft. Skip only for personal drafts where the user supplied everything needed.

Source check. Trigger when the document mentions a specific company, product, person, release date, version, funding round, metric, market fact, or technical spec — any current fact likely to change.

• Use primary sources before writing: user-provided material, official site, docs, filings, press release, app store page, or repo release.
• Keep a short note of source names and dates for facts that drive the document.
• If sources conflict or a fact cannot be checked quickly, ask the user instead of choosing silently.
• Avoid current-sounding claims ("latest", "recent", "new", version numbers, launch dates, financial figures) unless they are checked.

Material check. Trigger when the document is about a company, product, project, venue, or personal brand. Confirm the materials that make the subject recognizable before layout:

If a required item is missing, use a compact gap table and ask once. Do not replace missing material with generic imagery, approximate logo drawings, or invented values.

Materials status block. After the material check, output a structured status block before continuing. One-shot transparency display, not a question:

Materials status:
- Logo: OK assets/client-logo.svg
- Brand colors: OK #1B365D mapped to --brand
- Product screenshot: MISSING (proceeding with kami default placeholder)
- UI screenshot: not required for this doc type

Use OK, MISSING, or not required. If a required item is missing and no user input arrived, ask once with the gap table; otherwise continue silently.

Step 2 · Layout note (transparent, non-blocking)

Before creating the content set, write a short editor-style note stating the layout intent: doc genre, length target, narrative arc, embedded diagrams, material status. Match the user's language. Keep it under 80 words, written as prose, not a status panel. Continue immediately after; do not wait for approval.

Example (EN):

Layout intent: Equity Report (EN), two pages A4. Open with thesis and price target, run through valuation (DCF and comparables), close on catalysts and risks. A revenue line chart and an FY26 waterfall sit mid-doc. Logo is in hand; product image is absent, so the header stays text-only.

Example (CN):

排版意图：Equity Report 中文版，2 页 A4。先立论与目标价，进入估值 (DCF 与可比公司)，落于催化剂与风险。中段嵌一张营收趋势折线和 FY26 收入桥瀑 布。Logo 已就位，产品图暂缺，header 改走纯文字。

The note is for transparency, not approval. If the user pushes back, adjust; otherwise proceed to Step 3.

Step 3 · Create the content set

1. Pick a short content-set name (e.g. acme-whitepaper/).
2. Create the directory with an index.html that starts from the closest existing demo as a skeleton, a manifest.json, and a README.md.
3. Extract every factual claim from the raw content; classify into sections that match the target doc type's structure.
4. Gap-check: list what the layout needs but the content doesn't have. Share the gap table with the user before guessing.

Fit discipline — the kami authoring loop

Kami is a strict-page medium. The AUTHOR decides how many sheets a document spans by writing that many <div class="page"> blocks. Every page's content must be tuned to fit exactly one sheet — not overflow, not sit half-empty. This is kami's core discipline, adapted from the WeasyPrint-verified workflow in the upstream project.

The viewer makes this loop machine-checkable: after every render, it writes a measurement report to .pneuma/kami-fit.json. You MUST read this file after every meaningful edit and iterate until every page reports status: "fits".

Report shape:

{
  "content_set": "musk-resume",
  "file": "index.html",
  "paper": { "size": "A4", "orientation": "Portrait", "height_mm": 297 },
  "pages": [
    { "index": 1, "content_height_mm": 289.2, "overflow_mm": -7.8, "status": "fits" },
    { "index": 2, "content_height_mm": 314.5, "overflow_mm":  17.5, "status": "overflow" }
  ],
  "summary": { "overflow_count": 1, "sparse_count": 0, "fits_count": 1 }
}

The loop (run it automatically after every edit; don't wait for the user to point out overflow):

1. Make a content edit.
2. Read .pneuma/kami-fit.json.
3. If overflow_count > 0 → trim the overflowing pages → loop to step 2.
4. If sparse_count > 0 and content intent allows → enrich → loop to step 2.
5. When every page is fits → stop.

Reaching fits across every page is the quality bar before you tell the user the document is ready. Silence on your part implies the fit is passing. See references/cmd-fit.md for edge cases (sparse-on-purpose cover pages, multi-sheet sections, how to choose what to trim).

Per-page density target (multi-page docs only)

Applies to long-doc / portfolio / slides / equity-report / changelog. Does not apply to resume / one-pager / letter — those have their own length contracts.

Body-page fill target is 60–80%. Cover, table-of-contents, and final sign-off pages are exempt. This rule guards against AI-generated drafts that fragment content too thin to fill the sheets they occupy. The fill percentage is content_height_mm / paper_height_mm from kami-fit.json; the existing sparse status (overflow_mm < -50 ≈ <~83% on A4) already flags the worst cases — the per-template thresholds below sharpen the decision for borderline pages.

Items-per-page contract (thresholds from upstream V1.5.0):

Sparse-page merge rule. Any body page rendering under 50% full (i.e. kami-fit.json reports status: "sparse" and the items-per-page floor for the genre is breached) → apply, in order:

1. Merge upward into the previous section.
2. Merge downward into the next section.
3. Promote a list to a small diagram or table that earns the space.
4. Pin a .co callout to the bottom (slides only). Whitespace above a pinned callout is intentional, not sparse.

Forbidden ways to "fill" a sparse page: padding with filler prose, repeating the heading as a sentence, inventing statistics, restating the prior page in different words. If the merge options don't apply, the page itself shouldn't exist — delete the <div class="page"> block.

Last-page exemption. The last body page is allowed 40–60% fill; forcing balance there usually means padding. The cover and closing colophon may have any fill level.

Image generation (only when the user has configured a key)

A script lives at {SKILL_PATH}/scripts/generate_image.mjs. Default model is gpt-image-2 (fal.ai) — the right choice for kami because it renders legible typography inside images: figure captions, diagram labels, mock book spines, imagined postage stamps, rendered monograms. Opt in to --model gemini-3-pro only for painterly / watercolor / woodcut-style decorative artwork.

Images here live on a printed paper page. That constraint is absolute and distinguishes kami from every other Pneuma mode. The images can't look like they escaped from a SaaS landing page.

The kami image slop test

Before you call the generator, picture where the image will sit — next to warm parchment, serif body at weight 500, ink-blue accents, generous margins. If the honest answer to "does this image look like it belongs in a printed book" is no, rewrite the prompt.

Reject on sight:

• Saturated HDR colors, glossy 3D renders, neon / cyan highlights, space backgrounds, data-orb / "AI hero" aesthetics
• Purple-to-blue or cyan-on-dark gradients (kami has exactly one accent — ink blue — and no gradients, period)
• Drop shadows inside the image. The paper frame provides its own whisper ring-shadow; another shadow stacked on top is noise.
• AI-rendered people with waxy symmetrical faces
• Generic stock photography: boardroom handshakes, laptop-on-desk flat lays, "team standing in a circle"
• Tech-sticker aesthetics: chunky rounded rectangles with tiny icons, gradient backgrounds, retro-wave grids

Lean toward:

• Documentary / editorial photography — muted warm neutrals, diffuse natural light, analog film grain, print magazine composition
• Risograph / woodcut / letterpress illustration — limited palette, visible mark-making, handmade quality
• Duotone / warm monochrome portraits — ink blue + bone, or sepia + parchment; never full-color high-saturation headshots
• Technical drawings & schematics — thin ink lines on parchment, annotated with serif labels, in the spirit of 19th-century engineering manuals
• Mock objects on paper ground — a rendered museum label, a ticket stub, a book spine — imagined as if sitting on the page itself

Prompt discipline

Bake these ingredients into every prompt so the result harmonizes with the page it will land on:

1. Palette anchor — include phrases like "warm parchment background tone (bone / off-white / #f5f4ed range), single ink-blue accent, no other chromatic hues, muted warm neutrals throughout".
2. Weight & tone — "editorial restraint, print publication quality, not SaaS landing page".
3. Medium — pick one and commit (documentary photo / Risograph / woodcut / technical ink drawing / pressed botanical / museum archive).
4. Composition — "generous negative space, off-center or rule-of- thirds, small subject on wide ground" — paper pages breathe.
5. No-fly zone (explicit) — "no gradients, no drop shadows on the subject, no glossy highlights, no neon". Models are suggestible; say it out loud.

Two worked examples:

Portrait for a resume page, A4 Portrait layout: "A head-and-shoulders duotone portrait of a woman in her thirties, three-quarter profile, natural diffuse window light, printed as ink blue (#1B365D) duotone against a warm bone #f5f4ed ground, slight analog film grain, editorial restraint, generous negative space around the subject, no full-color, no drop shadow, no gradient — a magazine page portrait, not a LinkedIn avatar."

Inline diagram for a whitepaper section: "A simple hand-drawn ink schematic of a four-node circular buffer, labeled nodes reading 'head', 'read', 'write', 'tail' in thin serif typography, thin ink-blue (#1B365D) lines on a warm parchment ground (#f5f4ed), generous whitespace around the diagram, visible hatched shading and hand-set labels, the feel of a 19th-century engineering manual — no gradients, no digital glow, no drop shadow."

How to call it

cd {SKILL_PATH} && node scripts/generate_image.mjs \
  "Your kami-aligned prompt here" \
  --aspect-ratio 4:3 \
  --quality high \
  --output-format png \
  --output-dir <workspace>/<content-set>/assets \
  --filename-prefix figure-01

Flag guidance in paper terms:

After generating

1. Embed inside a <div class="page"> with appropriate framing. Keep captions in small serif below the image if it's a figure.
2. Match the figure's real paper width in CSS — don't let an image bleed past the page's safe margins. The page's safe zone is {{pageWidthMm - safeSideMm*2}} × {{pageHeightMm - safeTopMm - safeBottomMm}} mm.
3. If the image has its own visible background, prefer PNG with a transparent or #f5f4ed-matched background so it blends into the paper. No extra box around it — the page is the frame.
4. Re-read .pneuma/kami-fit.json. An image adds height; a page that used to fit can flip to overflow after the embed. Loop the fit discipline until every page reads fits again.

Consistency across figures

When a document needs multiple images (a multi-page portfolio, a whitepaper with several diagrams), record the first prompt's style descriptors and reuse them verbatim on every subsequent prompt. Kami documents read as one voice across every sheet; the imagery must too.

Don'ts

• Don't add a second accent color, gradients, or hard drop shadows.
• Don't change paper size — it is locked in .pneuma/config.json. If the user wants a different size, tell them to create a new workspace.
• Don't edit tokens in _shared/styles.css casually. Aesthetic drift compounds fast.
• Don't modify .claude/ — runtime-managed.
• Don't try to render Python-driven slide decks in this mode; that's a separate (future) mode.

Diagrams (14 self-contained templates)

When a page benefits from a chart, pick the closest match from _shared/assets/diagrams/, copy the <svg> block out, and drop it inside a <figure> on the page. Don't link the file via <iframe> — diagrams are meant to live inline so they paginate with the surrounding text.

Read references/diagrams.md once before drawing — it has the selection guide, kami token map, and the AI-slop anti-pattern table.

Auto-select charts from data. When the page content includes numeric data, pick the right chart type and embed it without waiting for the user to ask. Decision tree (first match wins, from upstream V1.5.0):

When data fits multiple types, prefer the one that shows variance most clearly. Always embed inside a <figure> with a caption that states the insight, not just the data range.

Before drawing, ask: would a well-written paragraph teach the reader less than this diagram? If no, don't draw.

References (read on demand)

Load only what the task needs. Default to the lowest tier.