Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/raja21068/AutoResearchnpx agentmods add skills/raja21068/autoresearch/paper-slidesWrote 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/raja21068/autoresearch/paper-slides)<a href="https://agentmods.dev/skills/raja21068/autoresearch/paper-slides"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/paper-slides/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/raja21068/autoresearch/paper-slides"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/paper-slides.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00081 | $0.06130 |
| Opus 5 | $0.00041 | $0.03065 |
| Sonnet 5 | $0.00016 | $0.01226 |
| Haiku 4.5 | $0.00008 | $0.00613 |
Grade A, and why
paper-slides 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 7d 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.
This is a copy
97% identical to paper-slides — 39 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 619 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Slides: From Paper to Conference Talk
Generate conference presentation slides from: $ARGUMENTS
Context
This skill runs after Workflow 3 (/paper-writing). It takes a compiled paper and generates a presentation slide deck for conference oral talks, spotlight presentations, or poster lightning talks.
Unlike posters (single page, visual-first), slides tell a temporal story: each slide builds on the previous one, with progressive revelation of the research narrative. A good talk makes the audience understand why this matters before showing what was done.
Constants
- VENUE =
NeurIPS— Target venue, determines color scheme. Supported:NeurIPS,ICML,ICLR,AAAI,ACL,EMNLP,CVPR,ECCV,GENERIC. Override via argument. - TALK_TYPE =
spotlight— Talk format. Options:oral(15-20 min),spotlight(5-8 min),poster-talk(3-5 min),invited(30-45 min). Determines slide count and content depth. - TALK_MINUTES = 15 — Talk duration in minutes. Auto-adjusts slide count (~1 slide/minute for oral, ~1.5 slides/minute for spotlight). Override explicitly if needed.
- ASPECT_RATIO =
16:9— Slide aspect ratio. Options:16:9(default, modern projectors),4:3(legacy). - SPEAKER_NOTES = true — Generate
\note{}blocks in beamer and corresponding PPTX notes. Setfalsefor clean slides without notes. - PAPER_DIR =
paper/— Directory containing the compiled paper. - OUTPUT_DIR =
slides/— Output directory for all slide files. - REVIEWER_MODEL =
gpt-5.4— Model used via Codex MCP for slide review. - AUTO_PROCEED = false — At each checkpoint, always wait for explicit user confirmation.
- COMPILER =
latexmk— LaTeX build tool. - ENGINE =
pdflatex— LaTeX engine. Usexelatexfor CJK text.
💡 Override:
/paper-slides "paper/" — talk_type: oral, venue: ICML, minutes: 20, aspect: 4:3
Optional: Style reference (— style-ref: <source>, opt-in)
Lets the user steer the talk's structural rhythm (story beats, theorem density, figure density inherited from the source paper) toward a reference paper. Default OFF — when the user does not pass — style-ref, do nothing differently from before.
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.
- 7d ago First seen · 619 lines · 81 tokens per session scan A fc68c0ac572e
paper-slides is a skill published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 81 tokens to every session and 6,130 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to paper-slides, differing in 39 lines, and is treated as a copy.
Other skills, from other repositories
plotting-agent
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimentallog.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER…
plotting-agent
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimentallog.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER…
content-refinement-agent
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules, deterministic 0-100 decision bands (Accept/Minor/Major/Reject) that drive a target-met early stop, and a Devil's Advocate…
section-writing-agent
Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimentallog.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges…
outline-agent
Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimentallog.md, template.tex, conferenceguidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator…
paper-autoraters
Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Quality (side-by-side). TRIGGER when the…