paper-poster-html skill
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.
Is the paper-poster-html skill safe?
Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-09-28.
No findings.
Install the paper-poster-html skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git /tmp/Auto-claude-code-research-in-sleep mkdir -p ~/.claude/skills cp -r /tmp/Auto-claude-code-research-in-sleep/skills/skills-codex-gemini-review/paper-poster-html ~/.claude/skills/paper-poster-html
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
Override for Codex users who want Gemini, not a second Codex/Codex-MCP reviewer, to act as the reviewer. Install this package after skills/skills-codex/*.
Paper Poster (HTML): measurement-gated poster generation
Gemini overlay assurance: reviewindependence: cross-family and acceptancestatus: accepted.
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 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.
This overlay is identical to skills/skills-codex/paper-poster-html/ except that the two cross-model review calls go to Gemini through the local gemini-review MCP bridge instead of a spawned GPT reviewer agent. Follow the base mirror for everything not restated here (phases, gates, fix vocabulary, figure provenance, output contract).
Reviewer constants (overlay)
gemini-review MCP bridge.
- REVIEWERMODEL = gemini-review** — Gemini invoked through the local
mcpgemini-reviewreviewstart; never reuse a prior review job across review boundaries. Save the returned jobId, poll mcpgemini-reviewreviewstatus with a bounded waitSeconds until done=true, and treat the completed payload's response as the reviewer output.
- Fresh review job per call — start each review with
prompt, and pass rendered posters via imagePaths.
- The Gemini bridge cannot read your local files — paste the relevant content into the
configure. Do not silently degrade the cross-model reviews into self-review.
- If the gemini-review bridge is unavailable, stop and tell the user what to
Phase 1 step 2 — Cross-model content audit (Gemini)
mcp__gemini-review__review_start:
prompt: |
Audit a conference-poster content plan against its source paper.
## Poster content plan
[PASTE poster_html/POSTER_CONTENT_PLAN.md]
## Paper source (relevant sections)
[PASTE the paper sections backing the plan's claims — abstract, headline
results tables, method equations, theorem statements]
For EVERY claim, number, equation, and attribution in the plan, output one row:
| claim on poster | paper location | paper says (verbatim) | match? |
with match ∈ {OK, NUMERIC-MISMATCH, OVERCLAIM, MISSING-PRECONDITION,
NOT-IN-PAPER, SCOPE-NARROWED}. End with a count per category.Poll reviewstatus until done=true; save the response to posterhtml/CLAIM_EVIDENCE.md. Fix every non-OK row or record it as a user-acknowledged tradeoff.
Phase 6 — Final review (Gemini, multimodal)
All hard gates PASS + polish warnings zero-or-waived + executor visual score ≥ 9 first. Then:
mcp__gemini-review__review_start:
imagePaths: ["poster_html/poster_preview.png"]
prompt: |
Final print-readiness audit of a conference poster (image attached).
## Final poster text content
[PASTE the text content extracted from poster_html/poster.html]
## Gate report summary
[PASTE the overall/hard_failures/warnings fields of poster_html/GATE_REPORT.json]
## Claim→evidence audit
[PASTE 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, two-hue discipline, real paper figures central and inside their cards),
(4) gate-log coherence.
Verdict: PRINT-READY or NEEDS-FIX with a numbered, severity-ordered issue list.Poll mcpgemini-reviewreview_status with a bounded waitSeconds until done=true; treat the completed payload's response as the reviewer verdict.
The reviewer recommends; it does not edit. Any fix → back through Phase 4/5 gates — never straight to re-review.
Review tracing
Save both review jobs' raw responses per ../../shared-references/review-tracing.md to .aris/traces/paper-poster-html/_run/.
More skills from wanshuiyin/Auto-claude-code-research-in-sleep
- Aablation-plannerUse when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
- Aablation-plannerUse when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
- AalphaxivQuick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes an arXiv/AlphaXiv URL, or provides a bare arXiv ID for quick understanding - not for broad literature search.
- AalphaxivQuick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes an arXiv/AlphaXiv URL, or provides a bare arXiv ID for quick understanding - not for broad literature search.
- Aanalyze-resultsAnalyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.
- Aanalyze-resultsAnalyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says \"analyze results\", \"compare\", or needs to interpret experimental data.
- AarxivSearch, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
- AarxivSearch, download, and summarize academic papers from arXiv. Use when user says \"search arxiv\", \"download paper\", \"fetch arxiv\", \"arxiv search\", \"get paper pdf\", or wants to find and save papers from arXiv to the local paper library.
- Aauto-paper-improvement-loopAutonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\", \"论文润色循环\", \"auto improve\", or wants to iteratively polish a generated paper.
- Aauto-paper-improvement-loopAutonomously improve a generated paper via Claude review through claude-review MCP → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\", \"论文润色循环\", \"auto improve\", or wants to iteratively polish a generated paper.
- Aauto-paper-improvement-loopAutonomously improve a generated paper via Gemini review through gemini-review MCP → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\", \"论文润色循环\", \"auto improve\", or wants to iteratively polish a generated paper.
- Aauto-paper-improvement-loopAutonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\", \"论文润色循环\", \"auto improve\", or wants to iteratively polish a generated paper.