duke-nus-marp

duke-nus-marp is a skill for Claude Code, Codex from CHENyiru3/AI-Skills-Collections. It costs 66 tokens per session (1,500 once invoked), scanned A, original, MIT.

A workflow for creating and editing academic slide decks in Marp, a tool that turns Markdown text into presentations. It uses a saved Duke-NUS-style theme and Harvard author–date citations.

In plain words
What is it for?
It is for lab meetings, research talks, and other Duke-NUS-themed academic presentations. It helps create slides, apply the theme, add source-based citations, and check rendered output.
Why use it?
It gives research presentations a consistent visual style and citation format. It also helps keep the editable Markdown, theme assets, and rendered slides aligned.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the writing plugin — 14 skills shipped together

Good fit It is for lab meetings, research talks, and other Duke-NUS-themed academic presentations. It helps create slides, apply the theme, add source-based citations, and check rendered output.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chenyiru3/ai-skills-collections/duke-nus-marp
Install

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.

Any agent
npx skills add CHENyiru3/AI-Skills-Collections --skill duke-nus-marp
Clone the repo
git clone --depth 1 https://github.com/CHENyiru3/AI-Skills-Collections

Made for: Claude Code, Codex.

Or install writing, the plugin that ships this one along with the rest of its 14 skills.

Wrote 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.

agentmods badge for duke-nus-marp

README.md
[![agentmods](https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/duke-nus-marp/github.svg)](https://agentmods.dev/skills/chenyiru3/ai-skills-collections/duke-nus-marp)
Your own site
<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/duke-nus-marp"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/duke-nus-marp/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.

agentmods 80×15 button for duke-nus-marp

Your own site · 80×15
<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/duke-nus-marp"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/duke-nus-marp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,500 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.01500
Opus 5.5 $0.00026 $0.00600
Sonnet 5.5 $0.00013 $0.00300
Haiku 4.5 $0.00007 $0.00150

Measured 3d ago against content hash 0475b5df3678, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

duke-nus-marp 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 3d 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.

skills-market/writing/presentations/duke-nus-marp/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Duke-NUS Marp slides

Produce editable Markdown with the bundled Duke-NUS CSS, source-grounded Harvard citations, and checked renders. User-specified content, slide count, location, and citation variants take precedence over defaults.

Assets and scope

  • assets/duke-nus.css: 1280 × 720 theme, Arial, blue #00539B, orange #F5821F, gray #4D4F53, online logo at https://i.imgur.com/hh3DOb2.png. Preserve this URL unless the user requests a change.
  • assets/starter.md: minimal deck including Harvard references.
  • assets/example.md: layout examples with explicitly fictional citation placeholders.
  • references/marp-guide.md: read before authoring for syntax, class behavior, Harvard conventions, and export options.

The theme is a personal adaptation of the user's Duke-NUS PowerPoint, not an official template release. Use the bundled assets; no original machine-specific folder is required.

Work in the requested output directory. Read applicable local instructions, especially inside the Obsidian vault. Copy assets to the project before editing; do not modify the installed skill as part of making a deck. When an existing project has a customized theme or configuration, inspect and preserve it unless the user asks for replacement. Do not update vault indexes merely because slide sources live inside the vault.

Authoring decisions

  1. Inspect the supplied content and identify audience, purpose, and supported conclusions. Use reasonable assumptions for routine layout choices. Ask only for missing information that materially changes the talk.
  2. Select the needed layouts from the example, then replace the examples with the actual content. Do not force every deck to include every layout. Honor the requested slide count, including references and cover unless the user specifies otherwise.
  3. Keep one main point per slide. Preserve units, uncertainty, qualifiers, and attribution. Leave clear placeholders for missing data rather than inventing findings or sources.
  4. Use # for the masthead title and an immediately following ## for its optional subtitle. Both should fit one line on ordinary content slides. Use ### for body headings.
  5. Use local directives <!-- _class: ... --> to avoid leaking layout changes to later slides. Supported classes are title, section, closing, figure, compact, references, and center. Use _paginate: skip on covers/closing slides when excluding them from the count.
  6. Use plain Markdown for routine content. The optional columns / wide-left divs need blank lines around their Markdown contents and HTML rendering enabled. In the figure layout, the last paragraph is the caption. Contain scientific figures without cropping evidence.

Read the full file on GitHub · 72 lines

Files

What ships with it

5 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.

Changes

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.

  1. 3d ago First seen · 72 lines · 66 tokens per session scan A 0475b5df3678

Subscribe to this mod's changes

duke-nus-marp is a skill published in the GitHub repository CHENyiru3/AI-Skills-Collections (2 stars, last pushed 3d ago), licensed MIT. It adds 66 tokens to every session and 1,500 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-11-11.

Related

duke-nus-marp compared with skills from other repositories

duke-nus-marp next to 6 skills from other repositories
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