paper-poster-html

Files (31)

• DESIGN_FINAL.md
• IMPLEMENTATION_CONVENTIONS.md
• posterly-MIT.txt · LICENSES/
• NOTICE.md
• SKILL.md
• __init__.py · scripts/_posterly/
• canvas.py · scripts/_posterly/
• measure.py · scripts/_posterly/
• polish.py · scripts/_posterly/
• preflight.py · scripts/_posterly/
• render.py · scripts/_posterly/
• textutil.py · scripts/_posterly/
• verify_final.py · scripts/_posterly/
• asset_check.py · scripts/
• extract_pdf_figures.py · scripts/
• poster_check.py · scripts/
• preprocess_figures.py · scripts/
• render_preview.py · scripts/
• run_gates.py · scripts/
• style_check.py · scripts/
• COMPONENTS.md · templates/
• README.md · templates/
• landscape_4col.html · templates/
• landscape_hero.html · templates/
• portrait_2col.html · templates/
• acl.json · templates/tokens/
• cvpr.json · templates/tokens/
• generic.json · templates/tokens/
• iclr.json · templates/tokens/
• icml.json · templates/tokens/
• neurips.json · templates/tokens/

SKILL.md (first lines)

# Paper Poster (HTML): measurement-gated poster generation

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md):
> resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP)
> with `reviewer_route.py` through the canonical helper resolver, preserving this
> slot's tier, fresh contexts, source/image inputs and deterministic gates.
> Codex examples/pins below apply only to `backend=codex`; other routes use their
> own first-call/reply contract. Save the route and actual returned identity;
> unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual
> families/completion/scope. Forward invocation reviewer/model/effort overrides
> to reviewer-bearing children. Generation workers are unchanged.


One HTML file styled for an exact print canvas (`@page { size: W H }`), rendered to PDF
via Playwright print emulation. **Iterate by measuring, not eyeballing** — the screen
preview lies; only print emulation at the correct viewport tells the truth. Core gate
machinery is adapted from [posterly](https://github.com/Chenruishuo/posterly) (MIT, ©
2026 Ruishuo Chen — see `NOTICE.md` and `LICENSES/posterly-MIT.txt`); ARIS adds style
discipline gates, figure-provenance gates, the cross-model review loop, and the
anti-patch-loop fix vocabulary.

## Why this skill exists (the failure it prevents)

A predecessor pipeline produced a poster with **30+ colors, zero real paper figures, a
screen-pixel canvas, and tiny formulas floating in oversized boxes**, then spent 12+
review rounds making it *worse* — each round added a new badge color or bespoke SVG
patch. The cure is structural, not exhortative:

1. **Hard gates run before any aesthetic opinion** (alignment, style, assets must PASS
   first — a reviewer never sees an unmeasured poster).
2. **A closed fix vocabulary** — visual-review fixes can only touch design tokens,
   whole catalogued components, content rebalance, assets, or canvas choice. New inline
   styles / new hex values / bespoke decorations are structurally forbidden.
3. **Two-hue discipline as a machine check**, not a style suggestion.
4. **Real paper figures with provenance manifest**, or the gate fails.

## Mental model

```
paper (.tex / PDF) ──► content plan + claim→evidence audit (codex, fresh)
                              │
   figures extracted ─────────┤  FIGURE_MANIFEST.json (provenance, sha256)
   (real paper figures ONLY)  ▼
   template scaffold ──► fill ──► run_gates.py            ◄─── HARD, loop here
                                  preflight → style → asset → measure → polish
                              │ all hard gates PASS
                              ▼
                    Claude visual review (≤3 issues × ≤3 rounds, fix-vocabulary only)
                              │ score ≥ 9
                              ▼
                    codex final cross-model review (fresh thread, full HTML+PDF)
                              │ pass
                              ▼
                    verify-final → poster.pdf + GATE_REPORT.json
```

## Constants

- **SKILL_SCRIPTS** = `${CLAUDE_SKILL_DIR}/scripts` — all helpers are single-owner and
  ship inside this skill (Arch C). If the directory is missing the install is broken:
  abort and tell the user to re-install the skill (Policy A — the gates ARE the skill;
  never improvise replacements).
- **REVIEWER_MODEL** = `gpt-6-astra`, reasoning `xhigh`, **fresh thread per review call**
  (`mcp__codex__codex`, never `codex-reply` across review boundaries).
- **CANVAS** — from the venue's official spec, looked up live in Phase 0. Never assume.
  (Known anchor: ICLR 2026 main = 185×90 cm landscape per its official printing
  service; ICML/NeurIPS commonly 60×36 in landscape; workshop posters often 61×91 cm
  portrait. Specs change yearly — verify.)
- **PALETTE** — default = `templates/tokens/generic.json` (slate-blue `#2D5F8B` accent
  + gold `#C9A24A` highlight + neutrals) for **all** venues. Venue packs are opt-in via
  `— venue-colors: true`. Purple-dominant accents (hue 250–285) are banned unless the
  user passes `— allow-purple: true`.
- **AUTO_PROCEED = false** — wait for explicit confirmation at every 🚦 checkpoint.
- **OUTPUT_DIR** = `poster_html/` in the working directory.

## Workflow

### Phase 0 — Resume, dependencies, venue spec

1. **Resume**: if `poster_html/POSTER_STATE.json` exists with `status: in_progress`
   (< 24 h), resume from the saved phase.
2. **Dependencies** (degradation chain, in order):
   - Playwright + bundled Chromium → if missing, `python3 -m playwright install
     chromium` → if install fails but system Chrome exists, scripts fall back to
     `channel="chrome"` → if all fail: you may produce the content plan and scaffold
     only, label everything **"not print verified"**, and must NOT emit a final PDF.
   - `pdfinfo` missing → PyMuPDF reads PDF dimensions. At least one of
     pdftoppm / PyMuPDF must exist for PNG review renders.
   - MathJax: download `tex-svg.js` once into `poster_html/assets/mathjax/` and
     reference it locally in the HTML. CDN is acceptable only for drafts; the measure
     gate hard-fails on unrendered MathJax either way.
3. **Venue spec lookup (live)**: consult the venue's official poster-instructions page
   (search + fetch). Extract dimensions, orientation, font floor, logo policy,
   anonymity rules, file format. Record `{spec, source_url, retrieved}` into
   `POSTER_STATE.json` — specs change yearly; never reuse a cached spec silently.

**🚦 Checkpoint**: echo the venue spec table (canvas, orientation, source URL) and the
chosen template. Wait.

### Phase 0.5 — Design discovery (one AskUserQuestion batch)

Ask once, ≤4 questions: layout template (from `templates/README.md`), palette
(default generic pack / venue pack / custom within constraints), logos + venue mark
(paths or "none" — never fabricate; check the venue's logo policy), QR target (paper /
code / project page / none — generate **offline** with `qrencode` or python-`qrcode`;
never a remote QR-service URL). Persist answers in `POSTER_STATE.json` as
`design_decisions` — re-read before any later "improvement" so deliberate choices are
never reverted.

### Phase 1 — Paper ingest, content plan, claim audit

1. Read the paper source (`.tex` ideal; PDF otherwise). Extract: title/authors/affils,
   the 3–5 headline numbers, core method (equations verbatim), main results
   (tables/figures and what they show), takeaways. Build
   `poster_html/POSTER_CONTENT_PLAN.md` — what goes in which column, word budget per
   card. **Target density** (excluding table cells, captions, author line, footer):
   standard poster **550–850 words**; dense theory+empirical poster **750–1050 words**,
   allowed only when ≥2 compact components are used (`eqn-anatomy`, `flow-strip`,
   `derived-col`, `claim-pills`, `keybox--4`). Warn yourself below 500 words on a

From wanshuiyin/Auto-claude-code-research-in-sleep, MIT.

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