scientific-figure
Use when the user has scientific data (or a prompt alluding to scientific data) and wants a publication-quality figure made from it. A generator drafts and renders a figure that lands a frozen communication goal; an adversarial critic critiques it hard and grades it 1-5 per axis against a fixed rubric (message, aesthetic, clarity, integrity, and a conditional domain-completeness axis), aggregates to 0-100, and decides pass; the generator revises against the critic's findings until the grade clears a threshold or the budget is hit. Both roles may consult the literature (Semantic Scholar + arXiv
npx skills add gaasher/Agent-Loop-Skills --skill scientific-figure --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Scientific Figure Loop The artifact is a **scientific figure** (the rendered image + the `plot.py` that produces it). Each iteration **generates → critiques+grades**: a **generator** authors a rendering script and renders the figure to land the frozen `<goals>` message; an adversarial **critic** grades it 0-100 against the fixed `rubrics/rubric.md` and decides `pass`; the generator then revises against the critic's concrete `findings`. The loop runs until the grade clears `<pass_threshold>` or the budget is hit. All work happens on copies inside a sandbox; the user's data is copied in read-only and never edited. The cast (all in this folder): - `roles/generator.md` — drafts/revises `plot.py`, renders `figure.png` by running `<render_cmd>`, optionally grounds domain content via `<lit>`; writes `generation_notes.md`. - `roles/critic.md` — the adversarial grader: re-derives each rubric axis independently, spot-checks the figure's numbers against the data, optionally lit-checks domain completeness, and emits `schemas/critique.schema.json` (the grade + `pass` + executable findings). - `rubrics/rubric.md` — the **fixed** grading rubric (the critic never edits it). - `schemas/critique.s
- Why the critic grades itself (the honesty problem)
- When to use
- Setup
- The loop
- Ledger
- Constraints
- Stops
What does the scientific-figure skill do?
Use when the user has scientific data (or a prompt alluding to scientific data) and wants a publication-quality figure made from it. A generator drafts and renders a figure that lands a frozen communication goal; an adversarial critic critiques it hard and grades it 1-5 per axis against a fixed rubric (message, aesthetic, clarity, integrity, and a conditional domain-completeness axis), aggregates to 0-100, and decides pass; the generator revises against the critic's findings until the grade clears a threshold or the budget is hit. Both roles may consult the literature (Semantic Scholar + arXiv
How do I install it?
Run `npx skills add gaasher/Agent-Loop-Skills --skill scientific-figure --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 gaasher/Agent-Loop-Skills, a repository with 146 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.