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Get Started Free →Turn an academic paper PDF into a presentation deck (.pptx) end-to-end. Use this skill whenever the user wants to "make slides from a paper", "generate a deck from this PDF", "make a PPT from this paper", "generate slides from a PDF document", "make a deck from a research paper", or supplies a research paper PDF and asks for a .pptx out. Trigger even when the user only says "deck this paper" or "summarize as slides". This is the dedicated, self-contained skill for academic-paper-to-deck flows.
.claude/skills/quzhan51496-paper2slides/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 83% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 899% | 0% |
| case-20 | ✗→✓ | ▲ Improved | 215% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 112% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 132% | 0% |
Turn an academic paper PDF into a presentation-ready .pptx. This is a conductor skill: you make the editorial and design judgments, while the mechanical steps are handled by this skill's own self-contained scripts — PDF parsing via the MinerU cloud API (scripts/parse_pdf.py) and .pptx rendering via a PptxGenJS bridge (scripts/render_pptx.py). It orchestrates a "paper → outline → spec → render → QA" pipeline and depends on no other skill.
| Stage | Input | Output | Owner | |---|---|---|---| | 0.5. configure | user dialogue | <workdir>/config.json | you (AskUserQuestion to confirm three items: length tier + whether to run visual QA + color scheme) | | 1. extract | paper.pdf | paper_meta.json + figures_index.json + figures/ + pages/ + equations + hi-res figure/table crops (produced in one shot by the MinerU cloud API) | scripts/parse_pdf.py | | 2. outline | paper_meta.json | slide_outline.json | you (per references/outline-heuristics.md) | | 3. spec | slide_outline.json + figures | slide_spec.json | you (per references/design-style.md) | | 4. render | slide_spec.json | output.pptx | scripts/render_pptx.py (PptxGenJS bridge) | | 5. qa | output.pptx | pass / fail + fix list | content QA always runs; visual QA is gated by Stage 0.5's config.json/visual_qa |
See references/pipeline.md for the detailed per-stage protocol.
Invocation form:
/paper2slides <paper.pdf> [output.pptx] [--from-stage <name>] [--force]output.pptx omitted → <paper-dir>/<paper-stem>_slides/<paper-stem>.pptx; on a name collision the directory auto-appends _v2 _v3<paper-dir>/.paper2anything/slides/<paper-stem>/; when the paper directory is read-only, fall back to ~/.cache/paper2anything/slides/Python environment: all scripts run in the paper2anything conda environment. Command prefix conda run -n paper2anything --no-capture-output python -m scripts.<name> ... (the prefix can be omitted once conda activate paper2anything is in effect). Every -m scripts.<name> must be run from this skill's directory (the parent of scripts/), otherwise you get No module named 'scripts'; the prefix-omission convention is in references/pipeline.md §General Conventions.
The first step is always to resolve the workspace:
bashconda run -n paper2anything --no-capture-output python -m scripts.workdir resolve \ <paper.pdf> [--output <out.pptx>] --ensure
The returned JSON contains all the named paths (paper_meta_path, slide_outline_path, slide_spec_path, figures_dir, ...) and each stage's completion status. Every later stage references the paths in this JSON — do not assemble paths yourself; the rules are centralized in scripts/workdir.py.
Re-run semantics:
| Flag | Meaning | |---|---| | default | already-completed stages are skipped (judged by whether the output files exist) | | --force | ignore all markers and run everything | | --from-stage <name> | re-run starting from the named stage (the entry point for the long-lived "interactive mode") |
<name> ∈ {configure, extract, outline, spec, render, qa}. To go through the three pre-flight questions again, use --from-stage configure (overwrites the old config.json).
Execute in the order below. Each stage has a "completion test" — once its output file appears the stage counts as done, and is auto-skipped on re-run. Each stage in this section writes only three things: (a) the minimal action to do (including the command to type), (b) the single most error-prone pitfall, and (c) a pointer to the corresponding Stage in references/pipeline.md. The full protocol, prerequisites, common errors, and edge cases all live in pipeline.md; this section does not restate them.
After Stage 0 resolves the workspace and before Stage 1, use AskUserQuestion] to confirm three items with the user, and Write the answers to the Stage 0 JSON's config_path (<workdir>/config.json):
deck_length: concise / standard / detailed / auto (no page-count target, recommended)visual_qa: true (default, adds the soffice→jpg→subagent visual loop) / false (run only the cheap content QA)color_scheme: auto (default, Stage 3 matches a palette to the paper's character) / custom (the user describes a preference in one line, stored in config and parsed by Stage 3)config.json already exists and neither --from-stage configure nor --force is given, don't ask again — reuse the last configuration.deck_length page-count band mapping, and the prefill / downstream-consumption details are in references/pipeline.md §Stage 0.5; the config.json schema is in references/schemas.md.Use the MinerU cloud API (requires MINERU_API_TOKEN, configured uniformly in the paper2anything package-root .env; with no token it errors out immediately):
bashset -a; source <paper2anything package root>/.env; set +a # export the unified .env (includes MINERU_API_TOKEN) conda run -n paper2anything --no-capture-output python -m scripts.parse_pdf <paper.pdf>
Produces paper_meta.json + figures_index.json + pages/ + hi-res crops in one shot (the structured metadata comes directly from MinerU).
For --dpi tuning (default 300) and the known imperfections of MinerU parsing (e.g. the bbox sometimes pins the y start onto a subfigure caption), see references/pipeline.md §Stage 1.
> Pitfall: before entering Stage 2 you must run the > 4 checks at the end of references/schemas.md (title/authors/same-kind merge/missing key kind) to verify paper_meta.json; the check results are not written back to > paper_meta.json, but are reflected directly in the Stage 2 outline.
Input paper_meta.json + figures_index.json + config.json → output slide_outline.json (schema in references/schemas.md). Per references/outline-heuristics.md, set roles and order, and write each slide's title/bullets/figure_ref/speaker_notes. Pitfall: read config.json/deck_length first — auto does not constrain the slide count; a non-auto value is a soft target for outline granularity, and you must not cut core narrative roles just to hit a number (details in outline-heuristics.md).
After writing, validate that the JSON is well-formed with Python:
bashconda run -n paper2anything --no-capture-output python -c \ "import json,sys; json.load(open(sys.argv[1])); print('ok')" \ <workdir>/slide_outline.json
For the full protocol and common errors, see references/pipeline.md §Stage 2.
Input slide_outline.json + figures_index.json + figures/ + pages/ → output slide_spec.json. Per references/design-style.md, choose palette/fonts/layout_kind (avoiding consecutive repeats), and translate the content into elements. Pitfall: every number and term must have a source in paper_meta / figures_index — do not fabricate.
When you need an icon use kind:"icon"; for naming see the "Icons" section of references/pptxgenjs.md, and for the schema see the icon element in references/schemas.md.
When you need to crop a region from a full paper page:
bashconda run -n paper2anything --no-capture-output python -m scripts.page_screenshot \ <workdir> <page> <x> <y> <w> <h>
bbox uses relative ratios 0..1; fill the output relative path into the corresponding image element's path. Hard gate for cropping: the first call's bbox must be value-for-value equal to figures_index.json/captions[i].bbox, and you may not eyeball the full page before cropping the first version — for the full baseline and the QA re-crop loop see references/design-style.md §3 (skipping the first cut and going straight to eyeballing = violating §3). The Stage 3 key constraints (coordinates ≤ canvas / margin:0 etc.) are in references/pipeline.md §Stage 3.
bashconda run -n paper2anything --no-capture-output python -m scripts.render_pptx \ <workdir>/slide_spec.json <workdir>/output.pptx
The output is <workdir>/output.pptx; after a successful render, copy it to the final output_path given by Stage 0 (first mkdir -p its parent directory <paper-stem>_slides/). Pitfall: it depends on node+pptxgenjs (installed globally); if node is not on PATH the script errors. On failure, first --dry-run to generate only render/build.js and locate the spec problem. For prerequisites and common errors see references/pipeline.md §Stage 4.
Execute per the QA section below: content QA always runs, and visual QA is gated by config.json/visual_qa.
| Input | Default | |---|---| | output.pptx omitted | <paper-dir>/<paper-stem>_slides/ (containing <paper-stem>.pptx); on a name collision the directory appends _v2, _v3 | | work directory not writable in the paper directory | fall back to ~/.cache/paper2anything/slides/<paper-stem>-<hash12>/ | | re-run on the same paper | already-completed stages (output files already exist) are auto-skipped | | config.json already exists | Stage 0.5 skips the questions and reuses the last configuration; to change config use --from-stage configure | | Stage 0.5 not asked / visual_qa defaulted | deck_length=auto, visual_qa=true (run visual QA) | | --from-stage <N> | force a re-run from the named stage, without checking outputs | | --force | force a re-run of all stages (rare, only on a schema upgrade) |
Only the few classes that need your judgment / routing are listed (all technical recovery is in pipeline.md):
| Symptom | Handling | |---|---| | Stage 1 section count < 5 or > 15 | you manually add / merge during the Stage 2 check | | Stage 5 reports "card bottom half empty / unbalanced columns / bottom whitespace" | not soft — fix per the three-lever model in references/design-style.md "Principles for Fixing QA Issues" (adjust text amount > adjust bullet spacing > adjust image size, stackable), then --from-stage render to re-run | | user/QA reports "leader markers not aligned with text" | per references/design-style.md "Visual-Richness Recommendations" item A, batch-reset icon_y to the alignment formula + a final self-check, then --from-stage render to re-run | | skill triggered but the user only wants to "read the PDF" | mis-trigger — tell the user this skill builds a slide deck and ask whether to proceed; do not continue with paper2slides if they only want to read the PDF |
For the full error recovery (Stage 1/4 technical, annotation green box, dpi, figure_ref, etc.) see the "Error-Recovery Quick Reference" section of references/pipeline.md.
Apply the QA loop in references/qa.md (the self-contained "Verification Loop" — content QA + visual subagent review). Read config.json/visual_qa first; the key points:
markitdown checks placeholders / number consistency / bullets not lifted from the abstract / no leftover placeholder in the title.config.json/visual_qa == true: soffice→pdf→jpg→dispatch a single subagent to batch-review.slide_spec.json then --from-stage render to fully re-render before QA; the recheck rounds narrow per the Verification Loop — round 1 covers the full deck, from round 2 on look only at the pages flagged last round ∪ the pages changed this round, with a final full pass over the whole deck before convergence.--from-stage configure then --from-stage qa".For the verification loop and the base visual-subagent prompt template, see references/qa.md; for the full A/B protocol and the qa_log.json structure, see references/pipeline.md §Stage 5; for the visual subagent prompt's two added paragraphs, the three-lever fix model, and the recheck-narrowing details, see the "Visual Subagent Prompt for QA" + "Principles for Fixing QA Issues" sections of references/design-style.md.
This skill is self-contained — everything you need is under references/ in this directory:
| Confusion | Go here | |---|---| | MinerU parsing anomalies (missing figure / garbled text / misaligned table / lost formula) | references/pipeline.md §Stage 1 + scripts/lib/mineru_client.py (token, model_version, zip-download retry) | | PPT visual design, color palettes, layout choices, taboos | the "Design fundamentals" + "Avoid" sections of references/design-style.md | | PptxGenJS API usage, gotchas, icon generation | references/pptxgenjs.md (includes the academic icon-name table) | | QA flow and the visual-subagent prompt | references/qa.md | | Detailed JSON schema fields for each stage's output (including config.json) | references/schemas.md | | How sections map to slide roles | references/outline-heuristics.md | | Matching color/layout to the paper's scenario | references/design-style.md |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-09 | fail→pass | 29,840 | 2,667 | -91% | 1 | 1 | 0% | 2,428 | 4,455 | +83% | 0 | 0 | — |
case-01 | fail→fail | 6,894 | 6,416 | -7% | 1 | 1 | 0% | 1,097 | 4,368 | +298% | 0 | 0 | — |
case-02 | fail→fail | 10,338 | 6,700 | -35% | 1 | 1 | 0% | 872 | 4,268 | +389% | 0 | 0 | — |
case-03 | fail→fail | 34,900 | 6,949 | -80% | 1 | 1 | 0% | 6,201 | 4,393 | -29% | 0 | 0 | — |
case-04 | fail→pass | 2,861 | 3,828 | +34% | 1 | 1 | 0% | 458 | 4,577 | +899% | 0 | 0 | — |
case-20 | fail→pass | 10,703 | 6,040 | -44% | 1 | 1 | 0% | 1,578 | 4,968 | +215% | 0 | 0 | — |
case-05 | pass→fail | 9,620 | 5,836 | -39% | 1 | 1 | 0% | 1,685 | 4,994 | +196% | 0 | 0 | — |
case-06 | fail→pass | 13,520 | 14,976 | +11% | 1 | 1 | 0% | 2,628 | 5,575 | +112% | 0 | 0 | — |
case-07 | fail→pass | 11,970 | 3,020 | -75% | 1 | 1 | 0% | 1,942 | 4,514 | +132% | 0 | 0 | — |
case-08 | fail→pass | 9,379 | 5,238 | -44% | 1 | 1 | 0% | 1,428 | 4,913 | +244% | 0 | 0 | — |
case-10 | fail→pass | 14,073 | 5,347 | -62% | 1 | 1 | 0% | 2,194 | 4,884 | +123% | 0 | 0 | — |
case-11 | pass→pass | 13,383 | 5,459 | -59% | 1 | 1 | 0% | 2,125 | 4,807 | +126% | 0 | 0 | — |
case-12 | fail→pass | 5,373 | 3,743 | -30% | 1 | 1 | 0% | 883 | 4,610 | +422% | 0 | 0 | — |
case-13 | fail→pass | 11,485 | 2,565 | -78% | 1 | 1 | 0% | 2,302 | 4,497 | +95% | 0 | 0 | — |
case-14 | fail→pass | 7,130 | 2,422 | -66% | 1 | 1 | 0% | 1,173 | 4,414 | +276% | 0 | 0 | — |
case-15 | pass→pass | 2,884 | 3,000 | +4% | 1 | 1 | 0% | 469 | 4,512 | +862% | 0 | 0 | — |
case-16 | fail→pass | 12,987 | 4,572 | -65% | 1 | 1 | 0% | 1,825 | 4,788 | +162% | 0 | 0 | — |
case-17 | fail→pass | 10,095 | 5,568 | -45% | 1 | 1 | 0% | 1,610 | 4,936 | +207% | 0 | 0 | — |
case-18 | fail→pass | 13,538 | 6,530 | -52% | 1 | 1 | 0% | 1,929 | 5,025 | +160% | 0 | 0 | — |
case-19 | pass→pass | 10,930 | 6,091 | -44% | 1 | 1 | 0% | 1,797 | 5,077 | +183% | 0 | 0 | — |
case-21 | fail→pass | 6,645 | 3,171 | -52% | 1 | 1 | 0% | 1,026 | 4,528 | +341% | 0 | 0 | — |
case-22 | fail→pass | 7,020 | 2,584 | -63% | 1 | 1 | 0% | 995 | 4,407 | +343% | 0 | 0 | — |
case-23 | pass→pass | 4,223 | 2,764 | -35% | 1 | 1 | 0% | 578 | 4,403 | +662% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 19 counted toward the lift figure. The other 4 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +61 percentage points is the difference between those two pass rates over the 19 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.