Agent skill · Code Review & Quality

paper-narrative

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.

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claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill paper-narrative --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 3 KB
Bundled scripts: yes
Path: skills/claude-science/paper-narrative/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# paper-narrative **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-fi

What's inside
Steps it walks through
  1. When to load
  2. Workflow
  3. Minimal invocation
Ships with 1 file
  • kernel.py
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About this skill
What does the paper-narrative skill do?

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.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill paper-narrative --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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