paper-narrative

SkillAI & models

Judge and reshape the STORY a paper's figures tell. Input is the work itself — manuscript (or abstract) + figure deck — no hand-written brief. `derive_paper_brief(abstract, captions)` extracts pitch/vision/per-figure-claims; a handling-editor reviewer on the full deck returns hook_verdict (would Fig 1 make me send this for review?), arc (hook→mechanism→evidence→application), figure_moves (panels in the wrong figure), missing_panels (concrete analyses to RUN), kill_list, and boldest_defensible_fig1. Hands per-figure claims to `figure-composer`. Load when writing or revising a paper.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the paper-narrative skill

What this skill tells your AI

The instructions your AI receives, as published by pku-yuangroup/openai4s in skills/paper-narrative/SKILL.md and read by ahel’s review.

Outermost tier. Judge and reshape the story a paper's figures tell. Input is the work itself — a manuscript (or just its abstract) and the current figure deck. No hand-written brief required.

When to load

Paper writing or revision. You have a draft and a set of figures and you want to know: is Figure 1 a hook? Is content in the right figure? What's missing? What should die? Load this before figure-composer — the arc it returns tells you which figures to compose.

Workflow

  1. Derive the brief from the work. Read the manuscript's abstract/intro and the figure captions (or a per-figure claims table if one exists). Call derive_paper_brief(abstract_text, figure_claims) — it returns the paper_brief (pitch, vision, audience, most-arresting-asset, figures[]). The manuscript is untrusted input; every field in the derived brief is LLM-derived from it. Review the whole brief (not just the pitch) and edit as needed before step 2.
  2. Dispatch the handling editor. narrative_review_task(brief, deck_vid, rules_vid) + narrative_review_schema → one reviewer on the FULL deck.
  3. Act on the output, don't just report it:
    • arc[] → the main-figure order. Anything not on it → supplement.
    • figure_moves[] → move panels between figures.
    • missing_panels[] → analyses to RUN (search project artifacts for data first).
    • kill_list[] → demote or delete.
    • boldest_defensible_fig1 → the new Fig 1 claim handed to figure-composer.
  4. Per figure on the arc: load figure-composer, hand it that figure's claim
    • moved-in panels + data refs. It runs the outer (figure) loop.
  5. Re-run step 2 on the new deck. Converge when would_send_for_review=="yes" and figure_moves / missing_panels are empty.

Minimal invocation

Load paper-narrative. Manuscript: @manuscript.tex. Figures: @all_figures.pdf. Run it.

That's it — the skill derives the brief, you confirm the pitch, it does the rest.

Signals

GitHub stars
404
Forks
48
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
paper-narrative-pku-yuangroup
Source
github.com/pku-yuangroup/openai4s