mcpbeat

Paper Poster Html

wanshuiyin/auto-claude-code-research-in-sleep-paper-poster-html

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.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
14221
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill paper-poster-html

What it tells the agent to use

found in the instruction text
Bash runs shell commands — read the instruction before connecting

The instruction itself

5 sections, as written by the author

> 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: review_independence: cross-family and acceptance_status: 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)

  • REVIEWER_MODEL = gemini-review — Gemini invoked through the local

gemini-review MCP bridge.

  • Fresh review job per call — start each review with

mcp__gemini-review__review_start; never reuse a prior review job across review

boundaries. Save the returned jobId, poll mcp__gemini-review__review_status with

a bounded waitSeconds until done=true, and treat the completed payload's

response as the reviewer output.

  • The Gemini bridge cannot read your local files — paste the relevant content into the

prompt, and pass rendered posters via imagePaths.

  • If the gemini-review bridge is unavailable, stop and tell the user what to

configure. Do not silently degrade the cross-model reviews into self-review.

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 review_status until done=true; save the response to

poster_html/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 mcp__gemini-review__review_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/<date>_run<NN>/.

How to use it

Copy the folder

Take wanshuiyin/auto-claude-code-research-in-sleep-paper-poster-html from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.