figure-composer
Compose one publication-grade multi-panel figure. Entry from a one-line claim + data refs, OR from an existing figure via `derive_outline(png)`. Runs a per-figure loop: outline (12-col grid, per-panel ask + label_budget) → fan-out one sub-agent per panel (each loads `figure-style`) → tile + stamp letters → adversarial composite review with two-tier feedback (Tier-1 outline_revisions / Tier-2 per-panel violations) → regen affected panels, ≤3 rounds. Loads panel_task / compose_figure / compose_crops / composite_review_task / derive_outline into the kernel. For one standalone plot use `figure-sty
npx skills add BioTender-max/awesome-bio-agent-skills --skill figure-composer --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.
# Figure Composer — narrative → panels → compose → adversarial loop **Step 0.** Load `figure-style` alongside this skill — that is the design rules (and `apply_figure_style()` + helpers). Panel sub-agents will load it independently; you need it in context to write the outline and review the composite. Sub-agents run as the default profile and acquire the rules by loading the skill. ## Inputs - **claim** — one sentence the figure makes true to a reader who reads nothing else. - **data** — CSV/parquet artifact version_ids that ground every panel. - **width_mm** — target venue's column width (common: 85–89mm single, 174–183mm double; check the venue guide). ## 0. Where this sits `figure-composer` is the **outer tier**: make ONE multi-panel figure good. The **inner tier** is `figure-style` (loaded by every panel sub-agent — and load it yourself if you draw anything locally). The **outermost tier** is `paper-narrative` — if this figure is part of a paper, run that FIRST: it decides *which* figure to make and hands you the claim. For a standalone figure, start at step 1. ## Entry points (pick one) - **From a claim:** you have a one-sentence claim and data refs → write the outline (step 1
- Inputs
- 0. Where this sits
- Entry points (pick one)
- 1. Narrative → panel outline
- 2. Fan-out (one sub-agent per panel)
- 3. Compose
- 3.5 Look before you review (vision self-QA)
- 4. Adversarial self-review loop (two-tier, design rules held fixed)
- Anti-patterns
What does the figure-composer skill do?
Compose one publication-grade multi-panel figure. Entry from a one-line claim + data refs, OR from an existing figure via `derive_outline(png)`. Runs a per-figure loop: outline (12-col grid, per-panel ask + label_budget) → fan-out one sub-agent per panel (each loads `figure-style`) → tile + stamp letters → adversarial composite review with two-tier feedback (Tier-1 outline_revisions / Tier-2 per-panel violations) → regen affected panels, ≤3 rounds. Loads panel_task / compose_figure / compose_crops / composite_review_task / derive_outline into the kernel. For one standalone plot use `figure-sty
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill figure-composer --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.