Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add QuZhan51496/paper2anything --skill paper2postergit clone --depth 1 https://github.com/QuZhan51496/paper2anythingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/quzhan51496/paper2anything/paper2poster)<a href="https://agentmods.dev/skills/quzhan51496/paper2anything/paper2poster"><img src="https://agentmods.dev/badge/skills/quzhan51496/paper2anything/paper2poster/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/quzhan51496/paper2anything/paper2poster"><img src="https://agentmods.dev/badge/skills/quzhan51496/paper2anything/paper2poster.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.09155 |
| Opus 5 | $0.00038 | $0.04577 |
| Sonnet 5 | $0.00015 | $0.01831 |
| Haiku 4.5 | $0.00008 | $0.00915 |
Grade A, and why
paper2poster scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper2Poster — Conference Poster Skill (You as Conductor)
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.
How you run this skill
This skill only works if you execute it as a sequence of small Bash + Read + AskUserQuestion turns. Do not try to short-circuit it.
- Run one step at a time with the
Bashtool, 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 withexport SKILL_DIR=<…>/paper2anything/paper2poster). - Read the intermediate artifact before moving on:
- after Step 3: the figures you considered, viewed in
parsed/figures/(and their captions indigest.json), and which sections you decided to carry with text instead, - after Step 5: your rendered
poster.png, plus your visual read and the blind-reader quiz result.
- after Step 3: the figures you considered, viewed in
- Pause for the user at the decision points with
AskUserQuestion:- After Step 2 — intake: size, venue, author block, visual policy.
- After Step 3 — is your per-section visual plan (which sections use an original figure, which use text) acceptable?
- After Step 4 — is the outline structure acceptable?
- After Step 8 — accept the poster, or revise/restyle it?
- Let the content decide whether a section gets a figure. Use an original paper figure where one genuinely helps; carry a section with text when no figure earns its place. Don't pad the poster with weak figures to hit a count, and don't strip a figure that's doing real work. A text-only section — or a text-only poster — is fine.
- Score every render, then iterate (Steps 5–7). After each render, run the deterministic geometry check and look at the PNG yourself (your visual read — hierarchy/density/balance/readability); run the blind-reader content quiz (Step 7) at milestones rather than on every micro-edit (it spawns a subagent, so it costs more than reading a PNG). Let what they surface drive the next edit; don't ship the first render unscored. The geometry check is two-sided: not just "no overflow" but also a fill ratio ≥ 0.95 — a poster that fits but leaves large whitespace (or shrinks text to do so) fails and must be iterated. Verify this gate yourself; how you reach it is your judgment.
- Don't overwrite a good render — keep scored candidates. Iteration is not always monotonic: an edit aimed at one issue can regress overall quality, and the version you had three edits ago may have read better. Before a non-trivial restyle or structural change, save the current render as a numbered candidate (e.g. copy
poster.html/poster.pngtoposter_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. - On error, stop and diagnose. Do not silently fall back to a degraded path to "make it run."
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/agent_design_rules_from_posters.md 4.5 KB
- references/color_palettes.md 1.7 KB
- references/layout_guide.md 3.0 KB
- references/poster_design_guide.md 5.2 KB
- references/poster_examples/cvpr2024_29230_poster.png 7167 KB
- references/poster_examples/cvpr2024_29245_poster.png 736 KB
- references/poster_examples/cvpr2024_29809_poster.png 3323 KB
- references/poster_examples/cvpr2024_31412_poster.png 1320 KB
- references/poster_examples/iclr2024_17503_poster.png 1634 KB
- references/poster_examples/iclr2024_17798_poster.png 969 KB
- references/poster_examples/iclr2024_18118_poster.png 1971 KB
- references/poster_examples/iclr2024_18324_poster.png 3075 KB
- references/poster_intake_qa.md 3.9 KB
- scripts/_env.py 683 B runs code
- scripts/auto_outline.py 21 KB runs code
- scripts/check_env.py 974 B runs code
- scripts/collect_figures.py 2.7 KB runs code
- scripts/geom_check.py 6.8 KB runs code
- scripts/parse_pdf.py 18 KB runs code
- scripts/screenshot.py 2.4 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 502 lines · 76 tokens per session scan A 360c7ef934d0
paper2poster is a skill published in the GitHub repository QuZhan51496/paper2anything (416 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 76 tokens to every session and 9,155 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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