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Convert academic papers (PDF) into conference posters (HTML/PNG). You are the conductor: you decide what each section needs — an original paper figure or text — write the outline, hand-author the poster HTML, and iterate on the render using your own visual read and a blind-reader content quiz.
Passed 11 of 16 test cases with the skill, and 4 of 16 without it.
and 9 more in the full report
11 fixed5 passed either way6 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
When setting up the environment to run the conference poster conversion scripts, what exact CLI command should be run to verify the unified conda environment setup, and what fallback command installs the browser automation component if missing?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies running check_env.py inside the paper2anything conda environment using conda run. | Missed | Passed |
| Specifies running playwright install chromium to install required browser binaries. | Missed | Passed |
The instructions your model reads when the skill loads.
Convert a paper PDF into an academic conference poster (HTML/PNG) by walking a small set of CLI scripts. You are the conductor: this file is the recipe, not an orchestrator. There is no run_pipeline.py — at each step you run one Bash command, read the intermediate artifact, and ask the user for confirmation at the decision points below.
PDF
→ parse_pdf.py (MinerU → content.md + figures/)
→ intake QA (you ask size/venue/authors/visual policy)
→ auto_outline.py (digest.json + assets[])
→ choose visuals (you read parsed/figures/ + captions: which sections use an original figure, which use text)
→ outline.json (you write from content.md; user confirms)
→ poster.html (you hand-author the poster: original figures where they help, text elsewhere)
→ render + score (Playwright PNG → deterministic geometry check + your own visual read + blind-reader content quiz)
→ iterate on poster.html (edit + re-render + re-score until it reads like a real poster)
→ poster.png
problem_context, method_main, and result_evidence are a useful reading-order spine to think about — what's the paper about, how does it work, what's the evidence. For each, decide what carries it best: an original paper figure if one reads well at poster scale, or text (a worded explanation, a labelled box, a short list) if no figure fits. There is no figure quota — use as many or as few original figures as the content calls for, down to zero. A text-only section, or a text-only poster, is a legitimate outcome when the figures don't earn their place.
This skill only works if you execute it as a sequence of small Bash + Read + AskUserQuestion turns. Do not try to short-circuit it.
Bash tool, exactly as written below. Use absolute paths under ${SKILL_DIR} (the directory this skill lives in — e.g. <…>/paper2anything/paper2poster; set it once per shell with export SKILL_DIR=<…>/paper2anything/paper2poster).parsed/figures/ (and their captions in digest.json), and which sections you decided to carry with text instead,poster.png, plus your visual read and the blind-reader quiz result.AskUserQuestion:
poster.html/poster.png to poster_candN.html/poster_candN.png) and record its scores. Pick the final from the best-scoring candidate, not just the latest edit. Never let a higher-scoring intermediate be silently overwritten by a worse one.test cases passed, vs 4 / 16 without
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