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 Yila-AI/awesome-research-skills --skill research-presentationgit clone --depth 1 https://github.com/Yila-AI/awesome-research-skillsWrote 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/yila-ai/awesome-research-skills/research-presentation)<a href="https://agentmods.dev/skills/yila-ai/awesome-research-skills/research-presentation"><img src="https://agentmods.dev/badge/skills/yila-ai/awesome-research-skills/research-presentation/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/yila-ai/awesome-research-skills/research-presentation"><img src="https://agentmods.dev/badge/skills/yila-ai/awesome-research-skills/research-presentation.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 | $0.00097 | $0.02160 |
| Opus 5 | $0.00048 | $0.01080 |
| Sonnet 5 | $0.00019 | $0.00432 |
| Haiku 4.5 | $0.00010 | $0.00216 |
Grade A, and why
research-presentation 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.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Presentation
Turn a paper or research corpus into a presentation that an audience can follow, verify, and discuss. The core promise is paper to slides without losing the evidence: preserve source meaning, choose a cumulative narrative, make figures legible, keep claims bounded, and deliver an editable deck with notes and a rendered QA trail.
This Skill owns the workflow from source inspection through final slide QA. It does not replace the author's scientific judgment, invent results, or silently strengthen a claim.
Route the request
Choose the narrowest route that satisfies the request:
| Input / request | Route |
|---|---|
| One or more PDFs, papers, or manuscripts | Full paper-to-slides workflow below; read references/paper-extraction.md first |
| Research notes, tables, figures, or a protocol | Evidence-led presentation workflow; mark unsupported fields instead of filling them |
| Existing PPTX to revise | Inspect the source deck, preserve its visual contract when requested, then run the same render/QA loop |
| A presentation brief with no source document | Skip extraction, but still create a claim ledger, narrative outline, source/asset notes, and visual QA |
| “Make it prettier” or “change the style” | Diagnose the current deck before editing; preserve scientific content and citations |
Before building, infer one sentence:
By the end, [audience] should [understand/decide/discuss] because [central evidence-backed takeaway].
Ask at most one blocking question when a missing choice would change the deck materially (for example, defense versus journal club). Otherwise make a conservative assumption and state it in the run log.
Non-negotiable contracts
- Evidence first. Read the source before planning the slide sequence. Never use a figure, number, table cell, citation, mechanism, or limitation that is not traceable to the supplied source or an explicitly cited external source.
- Bounded claims. Preserve population, setting, time frame, comparison, uncertainty, and claim strength. Distinguish author conclusions from presenter interpretation and label the latter.
- One narrative job per slide. Use takeaway titles that answer the question raised by the previous slide; do not build an inventory of paper sections.
- One visual anchor per content slide. Use a readable original figure/table, a meaningful metric, or a simple source-faithful diagram. Avoid decorative diagrams and generic stock imagery.
- Readable before complete. Start body text at 12 pt (11 pt floor), titles at 28–32 pt, cover title at 40–56 pt, and keep sub-11-pt characters below 10% of the deck. Add a slide or cut copy instead of shrinking type.
- Source anchors everywhere. Every content slide carries a visible anchor such as
Fig. 2,Table 1,§3.2, orp. 7; speaker notes include a[Sources]block for claims and assets. - No silent raster-only handoff. Prefer native/editable text, tables, shapes, and charts. Use source figures as images when needed, but preserve their aspect ratio and provide the original asset or source map.
- Render before delivery. Render every final slide, inspect the full-size pages, run overflow/coverage/font checks, and fix unintended overlap, clipping, wrapping, stretched figures, and empty placeholders.
What ships with it
10 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.
- agents/openai.yaml 279 B
- NOTICE 1.4 KB
- references/layouts.md 6.4 KB
- references/narrative-planning.md 1.8 KB
- references/paper-extraction.md 2.3 KB
- references/qa-contract.md 1.4 KB
- references/rendering.md 1.2 KB
- references/themes.md 18 KB
- scripts/audit_pptx.py 2.4 KB runs code
- scripts/render_slides.py 1.6 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.
- 7d ago Changed · +1 lines 6326448e157b
- 12d ago First seen · 151 lines · 97 tokens per session scan A e2ba7cd927af
research-presentation is a skill published in the GitHub repository Yila-AI/awesome-research-skills (119 stars, last pushed 7d ago), licensed Apache-2.0. It adds 97 tokens to every session and 2,160 once invoked, about $0.0005 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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