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Scholar Slides

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scholar-slides

Scholar Slides is an Agent Skill for documents published in the luwill/research-skills repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Use when the user wants a research paper, arXiv/DOI link, or research topic turned into academic slides — journal club / lab meeting (组会汇报), thesis defense (答辩幻灯片), conference or job talk (学术报告), poster, or grant pitch — or shares a paper and asks to "make slides / 做成 PPT / 讲一下这篇论文", especially when equations, numbers, figures, and citations must stay accurate and editable. NOT for marketing/pitch decks with no scholarly source, and NOT for writing the paper itself.

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/luwill/research-skills/blob/HEAD/scholar-slides/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/scholar-slides, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

scholar-slides

Turn a research paper (or topic) into a fidelity-first academic slide deck. Academia inverts the priorities of a normal deck tool: source fidelity > polish, evidence > persuasion, editability > flash. Equations, tables, numbers, figures, and citations stay true text/vector and traceable to the source — never rasterized by an image model, never fabricated.

Design rationale and the survey it is built on live in docs/; build plan in IMPLEMENTATION_PLAN.md.

Locked stack (see docs/03-design-proposal.md §0)

  • Render backend: reveal.js + KaTeX → vector PDF (Playwright). Editable PPTX / Beamer later.
  • Default deck type: lab meeting / journal club (组会) — reading-first, high density.
  • Citations: Zotero-first (mcp__zotero__*), Crossref/arXiv/DOI fallback.
  • Language: bilingual, English-default.

The non-negotiable integrity gate (ALWAYS on — see references/integrity.md)

Apply at every stage; enforced at Checkpoint 3:

  • Never fabricate numbers, citations, or figures. Everything traces to the source digest.
  • Math/tables/citations stay vector/text — never an image model's pixels.
  • Reuse real figures (bbox-cropped + Figure N [cite]); a conceptual schematic may be redrawn only if labeled "redrawn, not from source".
  • Flag, don't invent: an unresolved figure/number/citation emits a visible [MISSING: …] / [UNVERIFIED: …] placeholder surfaced to the user — never a silent fill.
  • Provenance is mandatory: every reused asset carries its source; every claim is traceable.

Pipeline (7 stages, 3 human checkpoints)

INPUT → 1.INGEST/DIGEST → [CKPT-1] → 2.DECK-TYPE → 3.OUTLINE → [CKPT-2]
      → 4.PER-SLIDE SPEC → 5.RENDER → 6.SELF-REVIEW(QA) → [CKPT-3] → 7.EXPORT
  1. Ingest → typed digest — references/ingestion.md. Run scripts/prepare_source.py <pdf|arXiv id|arXiv URL> to build the digest-input bundle (text, figure/table inventory with bboxes, cropped figures), then synthesize the typed paper digest from it (grounded in the bundle, never invented). → [CKPT-1] confirm the digest with the user (contributions, headline result, figure→slide map, any FLAGGED asset).
  2. Deck-type & parameters — references/deck-types.md. Pick deck type (default 组会), audience, time budget → slide budget, density register, required archetypes.
  3. Narrative outline — references/narrative.md. Re-sequence the paper into talk order; action-title per slide; arc-tension check. → [CKPT-2] approve the story arc.
  4. Per-slide spec — references/slide-spec.md. One self-contained, on-disk spec per slide (layout, content, equations, figures, citations, speaker notes).
  5. Render — references/math.md, references/figures-tables.md, references/citations.md, references/charts.md, references/design-system.md, references/export.md. reveal.js + KaTeX; real tables; real bbox-cropped figures (furniture-stripped; one panel per slide for multi-panel); data-bound redrawn charts; Zotero/BibTeX citations. Pick the visual theme via meta.theme (journal-club default / conference).
  6. Self-review QA — references/qa-self-review.md + references/integrity.md, then the aesthetics loop in references/aesthetics-review.md. Integrity scan + static validator + render screenshots + narrative/timing checks; the render pass also measures geometry deterministically (canvas voids, figure-text projected below the 12px legibility floor). Then score the rendered pixels on the 6-dimension rubric (adversarial persona), write the scores to <deck>/aesthetics_report.json (schema in aesthetics-review.md), and rework any slide with a dimension ≤ 2 or total < 18 until the report's rework list is empty — the QA gate flags a missing report (P3) and an unspent rework list (P2). It also nudges on bullet-ratio and layout monotony. → [CKPT-3] truth sign-off: review every [MISSING]/[UNVERIFIED] and generated asset.
  7. Export — references/export.md. Vector PDF (projection) + speaker notes + editable PPTX; verify the PPTX preserves the spec natively with scripts/verify_pptx_parity.py (protects the minimal-manual-edits promise). Regress the whole corpus with node scripts/run_benchmark.mjs.

Read only the reference file for the stage you are in (progressive disclosure — never glob references/). Each stage reads the confirmed artifact of the prior stage — the digest (Stage 1, user-confirmed at CKPT-1) and then deck.json — rather than re-deriving from the paper.

Scripts (scripts/)

Ingestion — pipeline stage 1 (Python, via ./.venv/bin/python; deps in requirements.txt):

  • prepare_source.py — Stage 1 entry point: PDF/arXiv → digest-input bundle.
  • ingest_pdf.py — PyMuPDF text+layout extraction; arXiv-id detection.
  • detect_figures.py — figure/table caption inventory + bounding-box localization.
  • crop_figure.py — clean single-figure bbox crop (no neighbor columns).

Deck build & render — pipeline stage 5 (Node, via node; deps in package.json, npm install + npx playwright install chromium):

  • build_deck.mjs — render entry point: deck.json → self-contained reveal.js deck.
  • render_deck.mjs — deck → one-page-per-slide vector PDF (and per-slide PNGs for QA).
  • lib/ — layouts (registered-layout lock), math (KaTeX), table, figure, escape, qa.

Citations & QA — pipeline stages 5–6 (citations = Python; QA = Node):

  • fetch_bib.py — citation resolver (arXiv/DOI/Crossref) with order-sensitive title verification.
  • qa_report.mjs — CKPT-3 gate: integrity scan + validate_deck.mjs + verify_slides.mjs + timing.

Speaker notes (Node):

  • speaker_notes.mjs — deck.json → notes.md handout + bilingual talk-length estimate.
  • lib/notes.mjs — timing + handout pure logic; design system in assets/templates/themes/.

Export & charts — pipeline stage 7 (export = Node; charts = Python):

  • export_pptx.mjs — deck.json → editable PPTX (native text/tables/notes; figures+equations as images).
  • make_chart.py — chart spec → data-bound Okabe–Ito plot (values plotted verbatim).

Tests: ./.venv/bin/python -m pytest (Python) and node --test tests/deck.test.mjs tests/qa.test.mjs tests/notes.test.mjs tests/pptx.test.mjs (Node).

Build status

The whole pipeline is implemented and validated on real papers. Not built: Beamer export, OCR for scanned PDFs, draft-deck ingestion; conference/答辩 deck types are authoring guidance in references/deck-types.md (no dedicated code). A deck is "done" only after the CKPT-3 human truth sign-off — the gate surfaces defects but cannot certify truth.