---
name: paper-poster-html
description: "DEFAULT poster pipeline — build an academic conference poster (ICML/NeurIPS/ICLR/CVPR/...) as a single HTML/CSS file with measurement-driven hard gates, real paper figures, a two-hue design-token system, and print-ready PDF via headless Chromium. Use when the user says \"做海报\", \"poster\", \"conference poster\", \"paper poster\", or asks to design/redo a research poster."
argument-hint: [paper-dir-or-pdf] [— venue: ICLR, canvas: 185x90cm landscape, venue-colors: true]
allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob
---

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

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` in the mainline
skill directory); 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 (fresh reviewer agent)
                              │
   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
                              ▼
                    executor visual review (≤3 issues × ≤3 rounds, fix-vocabulary only)
                              │ score ≥ 9
                              ▼
                    final cross-model review (fresh reviewer agent, full HTML+PDF)
                              │ pass
                              ▼
                    verify-final → poster.pdf + GATE_REPORT.json
```

## Constants

- **SKILL_SCRIPTS** — helpers and templates are single-owner and ship inside the
  mainline skill (Arch C) at `skills/paper-poster-html/scripts/` and
  `skills/paper-poster-html/templates/`. Resolve them in this order:

  ```bash
  SKILL_HOME=""
  [ -d ".agents/skills/paper-poster-html/scripts" ] && SKILL_HOME=".agents/skills/paper-poster-html"
  if [ -z "$SKILL_HOME" ] && [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills-codex.txt ]; then
      ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills-codex.txt 2>/dev/null) || true
  fi
  [ -z "$SKILL_HOME" ] && [ -d "skills/paper-poster-html/scripts" ] && SKILL_HOME="skills/paper-poster-html"
  [ -z "$SKILL_HOME" ] && [ -n "${ARIS_REPO:-}" ] && [ -d "$ARIS_REPO/skills/paper-poster-html/scripts" ] && SKILL_HOME="$ARIS_REPO/skills/paper-poster-html"
  [ -z "$SKILL_HOME" ] && [ -d "$HOME/.codex/skills/paper-poster-html/scripts" ] && SKILL_HOME="$HOME/.codex/skills/paper-poster-html"
  if [ -z "$SKILL_HOME" ]; then
    echo "ERROR: paper-poster-html scripts not resolved. Re-run the ARIS Codex install." >&2
  fi
  SKILL_SCRIPTS="$SKILL_HOME/scripts"
  ```

  If unresolved, the install is broken: abort and tell the user to re-install (Policy A
  — the gates ARE the skill; never improvise replacements).
- **REVIEWER_MODEL** = `gpt-5.5`, reasoning effort `xhigh`, **fresh reviewer agent per
  review call** (a new `spawn_agent:` every time; never reuse a reviewer agent 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.
     If print rendering, PNG review, or PDF verification is impossible in the current
     environment, stop and tell the user what to configure. Do not silently degrade
     this skill into an unmeasured text-only poster draft.
   - `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 question batch)

Ask the user 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
   4-column landscape (it will read as sparse next to professionally dense posters)
   unless the template is hero/visual-first; warn above 1100 unless the user asked for
   dense mode. Bullets ≤ 8 words when possible — density comes from *structure*, not
   long prose. **Prefer compact structure over prose**: if the paper contains an
   explicit objective, algorithm, theorem mechanism, or baseline comparison, extract at
   least two of: (1) empirical objective / loss stack; (2) term-by-term equation
   anatomy; (3) a method-flow strip grounded in paper variables; (4) a derived-Δ column
   for method-vs-baseline rows; (5) a 4-up implementation/theory keybox; (6) a
   claim/evidence pill table for numeric-heavy posters. **Do not invent an algorithm.**
   If the paper has only an objective, label the component "objective flow" or "loss
   anatomy", never "algorithm".
2. **Cross-model content audit** (fresh reviewer agent): give it the content plan path
   + paper source path(s) — paths only, no summaries — and ask for a claim→evidence
   table. Save to `poster_html/CLAIM_EVIDENCE.md`.

   ```text
   spawn_agent:
     model: gpt-5.5
     reasoning_effort: xhigh
     message: |
       Audit a conference-poster content plan against its source paper.
       Read these files yourself (no other context is provided):
       - poster_html/POSTER_CONTENT_PLAN.md
       - [paper source path(s)]
       For EVERY claim, number, equation, and attribution in the plan, output one row:
       | claim on poster | paper file:line | paper says (verbatim) | match? |
       with match ∈ {OK, NUMERIC-MISMATCH, OVERCLAIM, MISSING-PRECONDITION,
       NOT-IN-PAPER, SCOPE-NARROWED}. End with a count per category.
   ```
3. Fix every non-OK row or record it as a user-acknowledged tradeoff.

**🚦 Checkpoint**: content plan + audit summary. Wait.

### Phase 2 — Real paper figures (provenance-gated)

Source preference chain:
1. Paper source `figures/` (vector SVG/PDF → convert to SVG via
   `inkscape`/`pdf2svg` if available, else rasterize ≥ 2× rendered px).
2. PDF-only: `extract_pdf_figures.py contact-sheet` + `auto` to list candidate
   regions → pick crops (**🚦 human confirms crop choices**) → `crop` at 300–450 DPI.
3. Last resort: user supplies explicit `page,x0,y0,x1,y1` bboxes.

Then `preprocess_figures.py --autocrop` every asset. Every paper-derived image gets a
`FIGURE_MANIFEST.json` entry (source hash, page, bbox, dpi, sha256, natural_px) and is
embedded as `<img data-source="paper" data-asset-id="...">`.

**Hard rule**: ≥ 2 paper-derived visuals or the asset gate fails. Theory-only papers
may waive the *total-area* rule (`--waive-total-area`) at a human checkpoint — never
silently. Never draw bespoke decorative SVG "figures" as substitutes.

**Figure-area bands** (asset gate, fractions of *body*): total target **14–22 %**
(warn < 12 % / > 24 %, hard < 10 % / > 28 %); per ordinary figure target 4–8 % (warn
> 10 %, hard > 13 %); `figure--duo` combined 8–12 %. Hero templates pass `--hero`
(centerpiece may take 30–40 %). The failure mode is symmetric: too small reads as
decoration, too big crowds out content. Sibling figures that share axes or tell a
before→after story belong in one `figure--duo` card, not two cards.

### Phase 3 — Scaffold + tokens

`cp "$SKILL_HOME/templates/<chosen>.html" poster_html/poster.html`; retarget `@page`
+ `.poster` dims to the venue canvas (two edits, same values); apply the chosen token
pack onto the `:root` DESIGN TOKENS block; fill content per the plan; embed manifest
figures. Run `preflight` + `style_check` — both must PASS before any layout iteration.
(A fresh scaffold is *expected* to fail `measure` — that gate judges a filled poster.)

### Phase 4 — Layout hard loop

After every layout change:

```bash
python3 "$SKILL_SCRIPTS/run_gates.py" poster_html/poster.html \
    --tokens <pack.json> --manifest poster_html/FIGURE_MANIFEST.json \
    --report poster_html/GATE_REPORT.json
```

Canonical order: preflight → style → asset → measure → polish. Targets: column-bottom
**spread < 5 px** (aim < 3), footer gap ∈ [30, 50] px, intercard gap ∈ [12, 50] px,
canvas-fill ∈ [95, 101] %, poster bbox aligned to page within ±2 px. Fix guidance for
each failure mode lives in the gate output and `templates/COMPONENTS.md`. **Do not
proceed while any hard gate fails. Do not let a reviewer see an unmeasured poster.**
Balance under-filled columns with *content from the paper* (Gate C), never with
whitespace, `space-between`, or stretched cards.

### Phase 5 — Executor visual review (gated aesthetics)

Render and read the result yourself:

```bash
python3 "$SKILL_SCRIPTS/render_preview.py" poster_html/poster.html
pdftoppm -r 100 poster_html/poster_preview.pdf poster_html/review_full -png -f 1 -l 1
# plus 2-4 region crops at higher res (header / one column / equations) via PIL
```

Score strictly 1–10. **Critical caps**: < 2 real paper figures → ≤ 3; broken canvas /
clipped content / unreadable math → ≤ 4; ≥ 4 visible hue families or gradient-heavy
header → ≤ 4; large blank cards or columns → ≤ 5; fabricated visual claim → ≤ 3.
Checks: posterly-showcase gestalt (would this hang next to a professionally designed
poster without looking like a patched dashboard?), single-accent discipline, real
figures readable and central, print hierarchy (title → headline stats → figures →
detail), column fill, **equation prominence** (no tiny math in oversized boxes),
serif-body/sans-display pairing, no gradient kitsch, component consistency, 60-second
narrative. Output format:

```
SCORE: N/10
CAPS_TRIGGERED: ...
TOP_ISSUES: (max 3)
ALLOWED_FIX_TYPE per issue: token | component | rebalance | asset | template/canvas
PATCH_LOOP_RISK: low | medium | high
```

Loop: fix (fix vocabulary below) → re-run Phase 4 gates → re-score. **≤ 3 issues per
round, ≤ 3 rounds.** Score ≥ 9 → Phase 6. Still < 9 after 3 rounds → STOP patching;
escalate to template / canvas / content re-choice (back to Phase 3) or a human
decision. Never enter round 4 of cosmetic patching.

#### Fix vocabulary (closed set — the anti-patch-loop core)

Allowed: **(a)** edit a `:root` token value; **(b)** swap/remove/add a whole component
instance from `templates/COMPONENTS.md`; **(c)** content rebalance (move a card across
columns, trim/grow text *from the paper*, resize a figure within its AR band);
**(d)** template/canvas re-choice; **(e)** global edits to an existing component's CSS
that reference only tokens; **(f)** switching predefined variants (`.eqn--large`,
`.card--compact`, `.figure--wide`, `.nowrap`, …); **(g)** asset fixes (re-crop, swap
for a clearer figure from the same paper, re-preprocess).

Forbidden: new inline styles, new hex values anywhere, bespoke decorative SVG,
per-element font-size overrides. **A new component may not be born inside the visual
loop** — stop, get a human checkpoint, add it to `COMPONENTS.md`, re-run from Phase 3.

### Phase 6 — Final review (fresh reviewer agent, cross-model)

All hard gates PASS + polish warnings zero-or-waived + visual ≥ 9 first. Then a fresh
reviewer agent reviews the **final artifacts** (not the content plan) — paths only, no
executor framing:

```text
spawn_agent:
  model: gpt-5.5
  reasoning_effort: xhigh
  message: |
    Final print-readiness audit of a conference poster. Read these files yourself:
    - poster_html/poster.html (final single-file poster)
    - poster_html/poster_preview.png (rendered preview — view it)
    - [paper source path(s)]
    - poster_html/GATE_REPORT.json
    - poster_html/CLAIM_EVIDENCE.md
    Check: (1) fidelity & overclaims RE-CHECKED on the final text (polish introduces
    new claims), (2) residue (\ref{, TODO, raw < in math, missing images, remote
    URLs), (3) visual rhetoric (headline numbers prominent, banner readable from
    2 m), (4) gate-log coherence.
    Verdict: PRINT-READY or NEEDS-FIX with a numbered, severity-ordered issue list.
```

The reviewer recommends; it does not edit. Any fix → back through Phase 4/5 gates —
never straight to re-review.

### Phase 7 — Final verification + report

```bash
python3 "$SKILL_SCRIPTS/poster_check.py" verify-final poster_html/poster_preview.pdf \
    --from-html poster_html/poster.html --max-size-mb 20
```

Page count 1, dimensions match `@page`, size ≤ 20 MB, no TODO/residue, no remote
assets. Report: PDF path, final spread px, footer-gap range, gate summary table,
unresolved waivers, reviewer verdict. Update `POSTER_STATE.json` → `done`.

## State persistence

`poster_html/POSTER_STATE.json`: `{phase, venue, canvas{w,h,orientation,source_url,
retrieved}, template, token_pack, design_decisions{...}, figures_selected[],
visual_rounds, reviewer_verdicts{audit, final}, status, timestamp}` — written after
every phase; enables compact-recovery resume.

## Key rules

- **Measure, don't eyeball.** No layout claim without `run_gates.py` output.
- **Gates before aesthetics.** A reviewer only ever sees a poster whose hard gates
  PASS. This ordering is what kills the patch-loop death spiral.
- **Never invent paper numbers or figures.** Numbers come from the paper source;
  visuals carry manifest provenance. Fabrication = critical cap ≤ 3.
- **Two hues, one system.** Accent + gold + neutrals. The style gate enforces it;
  don't negotiate with the gate.
- **Real figures are the poster.** A poster without the paper's own figures is a
  dashboard, not a poster.
- **Fix vocabulary is closed.** If a fix isn't expressible as token / component /
  rebalance / asset / canvas, it's the wrong fix.
- **Cross-model verdicts.** The executor drives the loop and scores visuals;
  acceptance of content fidelity comes from the fresh reviewer agent (a loop can
  drive, never acquit).
- **Preserve user decisions.** Re-read `design_decisions` before "improving" anything.
- **Vendor boundary.** `poster_check.py`, `render_preview.py`, `_posterly/` are
  vendored from posterly — keep diffs minimal; ARIS-side logic goes in the new
  scripts, not in vendored files.

## Review tracing

Save every reviewer call's trace per `../shared-references/review-tracing.md` to
`.aris/traces/paper-poster-html/<date>_run<NN>/` (audit + final agents, raw responses).

## Output contract

```
poster_html/
├── poster.html              # single-file source of truth
├── poster_preview.pdf       # print-emulated, verify-final-checked
├── poster_preview.png       # thumbnail
├── POSTER_STATE.json        # resume state
├── GATE_REPORT.json         # canonical gate ledger (schema v1)
├── POSTER_CONTENT_PLAN.md   # what-goes-where + word budgets
├── CLAIM_EVIDENCE.md        # reviewer claim→evidence audit
├── FIGURE_MANIFEST.json     # figure provenance (sha256, page, bbox, dpi)
└── assets/{paper_figures,logos,qr,mathjax}/
```

## When NOT to use

- Slides, not a poster → `/paper-talk` / `/slides-polish`.
- The paper's headline isn't stable yet — fix the paper first; a poster amplifies
  whatever story it's given.
