name: present-paper description: > Academic presentation preparation — paper-driven (journal club, grand rounds, seminar) and lecture/teaching decks (course material, workshop slides, conference talks). Analyzes source material, finds supporting references, drafts audience-adapted speaker scripts, generates or augments PPTX with speaker notes, and prepares Q&A. triggers: present paper, paper presentation, journal club, seminar presentation, grand rounds, academic presentation, presentation prep, lecture, lecture material, teaching slides, course slides, 강의자료, 발표자료, 슬라이드, pptx tools: Read, Write, Edit, Bash, Grep, Glob model: inherit

Present-Paper Skill

Purpose

Prepare a polished academic presentation from a research paper. The skill walks through a 5-phase pipeline: paper analysis, supporting research, script writing, slide note injection, and Q&A preparation.

Use it when:

• preparing a journal club or seminar presentation
• presenting a paper for a graduate course
• preparing grand rounds or conference talks based on a published paper
• building speaker notes for an existing slide deck

Communication Rules

• Communicate with the user in their preferred language.
• Use English for medical, statistical, and methodological terminology.
• Add pronunciation guides for drug names and technical abbreviations in the user's language.
• Be direct about paper limitations, but frame them constructively.

Phase 0: Init & Outline

Required Inputs

Before starting, collect these from the user:

Paper Analysis

Read the paper and produce a structured analysis:

## Paper Analysis

### Citation
[Full citation with DOI]

### Background
- What gap does this paper address?
- What was known vs. unknown before this study?

### Study Design
- Type: [RCT / cohort / case series / meta-analysis / etc.]
- Subjects: [n, inclusion/exclusion]
- Methods: [key methodological choices]
- Primary outcome: [what was measured]

### Key Results
1. [Finding 1 with effect size and CI/p-value]
2. [Finding 2]
3. [Finding 3]

### Patient/Case Summary Table
[If applicable — structured table of individual cases or subgroups]

### Limitations
1. [Limitation 1]
2. [Limitation 2]

### Significance
- Why does this matter?
- What changes because of this paper?

Slide Outline

Create a slide-by-slide outline with time allocation:

## Slide Outline ([N] slides, [M] minutes)

| # | Title | Time | Key Content |
|---|-------|------|-------------|
| 1 | Title slide | 0:30 | Paper citation, presenter |
| 2 | Context / Prior sessions | 1:00 | How this connects to prior knowledge |
| 3 | Background | 1:30 | The gap this paper fills |
| ... | ... | ... | ... |
| N | Take-home messages | 0:30 | 3-5 key points |

Gate: User approves outline before proceeding.

Phase 1: Supporting Research

Search Strategy

Find references that strengthen the presentation:

1. Follow-up studies — Has the main finding been replicated or extended?
2. Clinical trial data — Large-scale data that contextualizes the findings
3. Review articles — Authoritative summaries that frame the topic
4. Contradicting evidence — Important for balanced Q&A preparation

Efficiency rule: Limit supporting references to 5-8 total. Only search categories that the approved outline (Phase 0) actually requires. Skip categories not needed for the presentation type (e.g., skip clinical trials for a methods-focused paper).

Selection Criteria

Do NOT summarize every paper found. Extract only:

• Specific data points needed for slides (incidence rates, OR/HR, AUC values)
• Findings that directly support or challenge the main paper
• Context that helps the audience understand significance

Output

## Verified References

### Main Paper
1. [Citation] — PMID: XXXXX, DOI: XX.XXXX/XXXXX

### Supporting References
2. [Citation] — PMID: XXXXX
   → Used for: [specific data point or context]
3. [Citation] — PMID: XXXXX
   → Used for: [specific data point or context]

### Key Data for Slides
- [Statistic 1]: [value] — Source: [Ref #]
- [Statistic 2]: [value] — Source: [Ref #]

Every reference must have a verified DOI or PMID. Mark unverified references with [UNVERIFIED].

Phase 2: Script & Content

Speaker Script

Draft a complete speaker script with these requirements:

1. Language: User's preferred language for narration; English for technical terms
2. Audience adaptation: Adjust explanation depth based on Phase 0 audience profile
   • For mixed audiences: add one-line plain-language explanations for specialty-specific terms
   • Example: "FLAIR sequence — an MRI technique that suppresses fluid signal to highlight edema"
3. Pronunciation guide: Include native-language pronunciation for drug names, abbreviations
   • Example: "lecanemab (leh-KAN-eh-mab)" or local equivalent
4. Timing markers: Note approximate time per slide
5. Transition phrases: Connect each slide to the narrative arc

Structure

## Speaker Script

### Slide 1: Title (0:30)
"[Opening — introduce yourself and the paper]"

### Slide 2: Context (1:00)
"[Connect to prior knowledge or clinical relevance]"

...

### Slide N: Take-home Messages (0:30)
"[Summarize 3-5 key points. Thank audience. Invite questions.]"

Extension Section (Optional)

Only include if user requested in Phase 0. Examples:

• AI/computational research directions stemming from the paper
• Clinical practice implications
• Policy or guideline implications
• Connections to the user's own research

Gate: User reviews script before proceeding.

Phase 3: Slides & Notes

Two Modes

Mode A: Generate new slide deck

Generate a fully-editable PPTX from structured inline data using python-pptx. Use the template library at ${CLAUDE_SKILL_DIR}/references/generate_pptx_templates.py as the canonical pattern — it ships a working showcase of every template type and a smoke-tested main().

Architecture

inline structured data (lists/dicts in build_*_slides())
    ↓ template functions (T_lead / T_text / T_table / ...)
editable PPTX with native text frames (selectable, restyleable in PowerPoint)

Three rules that keep slides stable:

1. No markdown parsing. Every slide is a function call with explicit inline data.
2. No cur_top cumulative position tracking. Use the fixed coordinate zones below — cur_top accumulates rounding errors and breaks layout after ~10 slides.
3. No Marp. Marp renders to images; the deck becomes uneditable and reviewers cannot copy text or restyle.

Slide-type templates

Figure source formats (when consuming /make-figures output)

When the deck pulls figures from analysis/figures/ produced by /make-figures:

• Preferred for slides: PNG at ≥300 dpi. python-pptx add_picture() handles this directly. Set img_pct (template T_image_right) so the figure occupies ≥40 % of slide width on a 13.33 × 7.5-in widescreen layout.
• Vector source available: prefer PDF only if the slide will be projected at >1080p or printed as a handout — convert PDF → PNG at the target DPI (pdftoppm -r 300 input.pdf out_prefix) before insertion, because python-pptx PDF embedding is unreliable across PowerPoint versions.
• Forbidden: TIFF (Mac PowerPoint silently drops it — see Mac compatibility checklist below); JPEG for line art (compression artifacts on diagonal lines); raw SVG (PowerPoint Mac handles it inconsistently).
• Caption / legend: re-draft for spoken-narration context, not the journal legend verbatim. The journal legend assumes a reader; the slide caption assumes a listener with 5–10 seconds of attention.

Helpers (used by templates — usually you do not call directly)

Design tokens (defaults — change to fit institution/journal)

NAVY    = #1B2A4A   # title text, section divider background
TEAL    = #0072B2   # subtitle, underline, table header bg, quote bar
ORANGE  = #D55E00   # highlight box border
GRAY    = #333333   # body text
FONT    = 'Apple SD Gothic Neo'   # use a Latin-only font on non-Korean decks

Fixed coordinate zones (16:9 = 13.333" × 7.5")

ML / MR = 0.8"     MT = 0.5"     CW = SW − ML − MR = 11.733"

TITLE_Y = 0.5"    TITLE_H = 0.8"
SUB_Y   = 1.3"    SUB_H   = 0.5"
BODY_Y  ≈ 1.9"    BODY_H  ≈ 5.1"

Build script responsibilities

A from-scratch generation script must:

• Convert TIFF images to PNG before add_picture (Mac PowerPoint silently drops TIFF).
• Apply EXIF transpose to iPhone photos before insertion.
• After inserting/removing slides, sync docProps/app.xml (<Slides>, <Notes>, HeadingPairs, TitlesOfParts) to the actual count, or PowerPoint Mac will raise a recovery dialog on open.
• If you copy <a:srcRect> from another deck, copy the values verbatim — they are 1/1000-percent (cap 100000), never EMU. A unit conversion bug here crops 99% of the image off-slide.
• Print slide count, notes count, file size, and editability check at the end.

Forbidden in Mode A

• ❌ Marp CLI for PPTX (always image-rendered, uneditable).
• ❌ Markdown auto-parsing into slides (layout drifts on every regeneration).
• ❌ cur_top cumulative top tracking (accumulates rounding error).
• ❌ Direct iPhone photo insert without EXIF transpose (rotated 90° in PowerPoint).
• ❌ Using python-pptx from-scratch rebuild to edit an existing deck — see Patch over Rebuild below.

Mac PowerPoint compatibility checklist

PowerPoint Mac is stricter than Windows / Keynote / LibreOffice on OOXML defects. Verify before delivering any deck destined for a Mac viewer:

Validation must run on PDF export AND Mac PowerPoint — neither alone catches all four. PDF misses sp3d outlines and srcRect corruption.

Patch over Rebuild — editing an existing PPTX

When the user supplies an existing deck and asks for surgical edits (textbox width, image crop, font swap, sp3d removal), prefer regex/sed patching of the unzipped XML over regenerating with python-pptx. From-scratch rebuild loses:

• <a:srcRect> image crops
• <a:sp3d> / <a:scene3d> (when intentional)
• Slide master / layout / theme details
• app.xml and core.xml metadata

unzip -q original.pptx -d /tmp/work
python3 -c "
import re; from pathlib import Path
p = Path('/tmp/work/ppt/slides/slide23.xml')
s = p.read_text()
s = s.replace('cx=\"9504720\"', 'cx=\"11200000\"')
p.write_text(s)
"
cd /tmp/work && zip -rq ../patched.pptx . -x '*.DS_Store'

python-pptx is reserved for (a) brand-new decks built via the templates above, or (b) appending speaker notes via slide.notes_slide.notes_text_frame.text. The skill's scripts/inject_speaker_notes.py is the canonical example of (b).

Standard structure (10–15 min paper talk)

1. Title slide (T_lead) — paper citation + presenter
2. Background (T_text × 1–2)
3. Study design / Methods (T_text or T_two_col)
4. Key results with figures (T_image_right / T_table × 2–3)
5. Discussion (T_text)
6. Limitations (T_two_col_with_box works well)
7. Take-home (T_text or T_highlight_slide)

Output

Save to output/presentation.pptx. Speaker notes go into the notes pane only — never modify slide design when adding notes.

Mode B: Add notes to existing slides (more common)

• Read existing PPTX to understand slide structure and count
• Map speaker script sections to corresponding slides
• Generate inject_notes.py script tailored to the specific presentation

Note Injection Script

Generate a tailored inject_notes.py following the pattern in ${CLAUDE_SKILL_DIR}/references/inject_speaker_notes.py. The generated script should contain only the notes dictionary customized for this presentation and the main injection loop from the template.

Critical Rule

Speaker notes are injected without modifying slide design, layout, text, or images. The script only touches the notes pane. Verify by comparing slide content before and after.

Phase 4: Q&A Preparation

Question Generation

Generate questions from multiple perspectives:

1. Methodology critics: "Why this design? Why not...?"
2. Domain experts: Deep technical questions about the specific field
3. Generalists: "What does this mean for clinical practice?"
4. Students/trainees: Clarification questions about unfamiliar concepts

Answer Structure

Every answer should follow the pattern:

Acknowledge → Evidence → Conclude

"That's an important limitation. [Acknowledge the concern honestly.]
However, [cite specific supporting evidence — author, year, finding].
So while [restate limitation], [conclude with the paper's contribution despite it]."

Quick Review Sheet

A single-page reference for last-minute review:

## Quick Review

### Must-Know Numbers
| Metric | Value | Source |
|--------|-------|--------|
| [Key stat 1] | [value] | [Ref] |
| [Key stat 2] | [value] | [Ref] |

### Common Pitfalls
- Don't confuse [X] with [Y]
- [Classification A] and [Classification B] are independent frameworks
- Slide says [rounded value], precise value is [exact value]

### Key Takeaways (memorize these)
1. [Point 1]
2. [Point 2]
3. [Point 3]

Output File Structure

All outputs go in the user's presentation directory:

{presentation_dir}/
├── _analysis.md              # Phase 0: Paper analysis + outline
├── _references.md            # Phase 1: Verified references + key data
├── _script.md                # Phase 2: Speaker script
├── _qa_prep.md               # Phase 4: Expected Q&A
├── _quick_review.md          # Phase 4: Pre-presentation review sheet
├── inject_notes.py           # Phase 3: Tailored note injection script
├── figures/                  # Extracted paper figures (if needed)
└── reference/                # Supporting paper PDFs (if downloaded)

Constraints

• Never fabricate references. Every citation must be verified against PubMed, DOI, or the PDF itself.
• Never modify slide design when injecting notes. Notes and slides are separate concerns.
• Always ask audience first. Do not start drafting until the target audience is defined.
• Extension sections are opt-in. Do not add AI/clinical/policy sections unless explicitly requested.
• Respect presentation time. Script length must match allocated time (roughly 130-150 words per minute for academic presentations).

Anti-Hallucination

• Never fabricate references. All citations must be verified via /search-lit with confirmed DOI or PMID. Mark unverified references as [UNVERIFIED - NEEDS MANUAL CHECK].
• Never invent clinical definitions, diagnostic criteria, or guideline recommendations. If uncertain, flag with [VERIFY] and ask the user.
• Never fabricate numerical results — compliance percentages, scores, effect sizes, or sample sizes must come from actual data or analysis output.
• If a reporting guideline item, journal policy, or clinical standard is uncertain, state the uncertainty rather than guessing.