Paper Poster HTML Agent Skill

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 (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:

• Hard gates run before any aesthetic opinion (alignment, style, assets must PASS

first — a reviewer never sees an unmeasured poster).

• 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.

• Two-hue discipline as a machine check, not a style suggestion.
• 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-5.6-sol, 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

• Resume: if poster_html/POSTER_STATE.json exists with status: in_progress

(< 24 h), resume from the saved phase.

• 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.

• 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

• 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".

• Cross-model content audit (fresh codex thread, xhigh): give it the content

plan path + paper source path(s) — paths only, no summaries — and ask for a

claim→evidence table: `| claim on poster | paper file:line | paper says (verbatim) |

match? |` with match ∈ {OK, NUMERIC-MISMATCH, OVERCLAIM, MISSING-PRECONDITION,

NOT-IN-PAPER, SCOPE-NARROWED}. Save to poster_html/CLAIM_EVIDENCE.md.

• 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:

• Paper source figures/ (vector SVG/PDF → convert to SVG via

inkscape/pdf2svg if available, else rasterize ≥ 2× rendered px).

• PDF-only: extract_pdf_figures.py contact-sheet + auto to list candidate

regions → pick crops (🚦 human confirms crop choices) → crop at 300–450 DPI.

• 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 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:

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 — Claude visual review (gated aesthetics)

Render and read the result yourself:

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

Calibrate first (../shared-references/taste-calibration.md): if

human-curated references/good/ + references/bad/ exist under this skill

dir (or the project supplies its own pair), score those 3+3 reference posters

on the axes below BEFORE the target, anchoring the scale. Never select, search

for, or generate anchors yourself; if no reference sets exist, proceed

uncalibrated and mark CALIBRATION: none — never fabricate anchor scores.

Axes (weights sum 1.0): Design 0.35 · Craft 0.30 · Functionality 0.20 ·

Originality 0.15. Mapping: `SCORE = min(round(1 + 9 × COMPOSITE), lowest

triggered cap) — caps apply AFTER the mapping, and the loop's Score ≥ 9`

threshold below always reads this final capped SCORE, never the raw

composite.

Score strictly 1–10. Critical caps (hard floors — a calibrated composite

never overrides them): < 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            (= min(round(1 + 9 × COMPOSITE), lowest cap); drives the loop)
COMPOSITE: 0.xx        (weighted; list the four per-axis scores)
CALIBRATION: anchored | none
GAP: <which reference poster the target falls short of / exceeds, on which axis, and why — one paragraph; omit only when CALIBRATION: none>
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 — Codex final review (fresh thread, cross-model)

All hard gates PASS + polish warnings zero-or-waived + visual ≥ 9 first. Then a fresh

codex thread (xhigh) reviews the final artifacts (not the content plan):

poster.html, the rendered PDF/PNG, the paper source, GATE_REPORT.json,

CLAIM_EVIDENCE.md — paths only, no executor framing. It checks: (1) fidelity &

overclaims re-checked on 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. 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

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, codex 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, codex_threads{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. Claude/codex review 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. Claude drives the loop and scores visuals; acceptance of

content fidelity comes from the fresh codex thread (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 codex reviewer call's trace per shared-references/review-tracing.md to

.aris/traces/paper-poster-html/<date>_run<NN>/ (audit + final threads, 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        # codex 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.