ablation-planner
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
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\",
$ npx -y skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill paper-poster-html --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/paper-poster-htmlContext preview
The summary Claude sees to decide when to auto-load this 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\",
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. Supersedes the retired LaTeX /paper-poster." argument-hint: "[paper-dir-or-pdf] [— venue: ICLR, canvas: 185x90cm landscape, venue-colors: true]" allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebFetch, WebSearch, AskUserQuestion, mcp__codex__codex
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.
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.
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.jsonship 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).
(`mcp__codex__codex`, never `codex-reply` across review boundaries).
(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.)
`— venue-colors: true`. Purple-dominant accents (hue 250–285) are banned unless the user passes `— allow-purple: true`.
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):
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.
pdftoppm / PyMuPDF must exist for PNG review renders.
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.
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 re
· · · · · · -orange?style=flat) · · 💬 Join Community · 💡 Use ARIS as a skill-based workflow in Claude Code / Codex CLI / Cursor / Trae / Antigravity / GitHub Copilot CLI / OpenClaw / DeepSeek Harness, or get the full experience with the standalone ARIS-Code
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes…
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to…
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper…
Autonomously 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\",…
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop…