nature_figure

Name: nature_figure
Author: ai4protein

244stars35forks

How to install nature_figure?

ai4protein/venusfactory2/nature_figure

$npx -y skills add ai4protein/VenusFactory2 --skill nature_figure

Installs into the current project.

Summary

Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially f

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SKILL.md

1	# Nature Figure Making — Router
2
3	This skill is split into two layers:
4
5	- A static layer under `static/` that holds versioned, reusable content fragments (the figure contract and default stance, plus a per-backend quick-start for Python and R).
6	- A dynamic layer (this file plus `manifest.yaml`) that detects the plotting backend and loads only the fragment needed for the current job. The large design, API, pattern, and QA material lives in on-demand references.
7
8	Do not try to apply the figure logic from memory or from this router. Always load fragments from disk as described below.
9
10	## Routing protocol
11
12	Follow these five steps every time the skill is invoked.
13
14	### 1. Load the manifest and the core layer
15
16	Read [manifest.yaml](manifest.yaml). It declares the `backend` axis, the allowed values, and the file paths each value maps to.
17
18	Also read every file listed under `always_load` (`static/core/contract.md` and `static/core/stance.md`). These hold the figure contract, the backend gate, the missing-runtime rule, the privacy rule, and the default operating stance that apply to every figure job.
19
20	### 2. Resolve the backend — a blocking gate
21
22	Backend selection blocks everything else. Decide the `backend` value only from an explicit user choice or a clearly language-specific input file/workflow:
23
24	- `python` — matplotlib / seaborn.
25	- `r` — ggplot2 / patchwork / ComplexHeatmap.
26
27	If the user has not explicitly chosen, ask exactly one concise question — Python or R? — and stop. Do not default, guess, generate mock data, or write scripts before the answer. Only recommend a backend when the user explicitly asks you to choose; then use `references/backend-selection.md`, state the reason, and proceed. Once selected, the backend is exclusive for all drawing, previewing, exporting, and visual QA (see `core/contract.md`).
28
29	### 3. Load the matching backend fragment
30
31	After the backend is resolved, Read the mapped fragment (`static/fragments/backend/python.md` or `static/fragments/backend/r.md`). It carries the backend-only execution rule and the publication quick-start (rcParams/theme and export helper). Do not load the other backend's fragment.
32
33	### 4. Build the figure using the loaded material
34
35	Apply the loaded material in this order:
36
37	1. Figure contract (`core/contract.md`) — write the core conclusion, map the evidence chain, classify the archetype, set the journal/export contract, before any code.
38	2. Default stance (`core/stance.md`) — archetype-first composition, hero panel, restrained palette, statistics/integrity as part of the figure.
39	3. Backend fragment — the exclusive Python or R quick-start and execution rule.
40
41	The chart serves the scientific logic; aesthetic polish is subordinate to making the core conclusion clear, defensible, and reviewable.
42
43	### 5. Reach for references only when needed
44
45	The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest — for example `references/figure-contract.md` to build the contract, `references/api.md` for the Python palette and helpers, `references/r-workflow.md` for R, `references/design-theory.md` for color/typography/export rationale, `references/common-patterns.md` and `references/chart-types.md` for layout/chart recipes, `references/nature-2026-observations.md` for real Nature page archetypes, `references/qa-contract.md` before final delivery, and `references/tutorials.md` / `references/demos.md` for worked examples.
46
47	## Why this split
48
49	- The static layer is versioned and reviewable. The backend gate is now explicit in the manifest rather than buried in prose.
50	- The dynamic layer keeps each invocation cheap: only the selected backend's quick-start enters context, and the 2,600+ lines of reference depth load only when a step needs them.
51	- The router itself is short on purpose. Update fragments and refe

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Type

nature_figure

244stars35forks

View on GitHub

How to install nature_figure?

ai4protein/venusfactory2/nature_figure

$npx -y skills add ai4protein/VenusFactory2 --skill nature_figure

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Nature Figure Making — Router
2
3	This skill is split into two layers:
4
5	- A static layer under `static/` that holds versioned, reusable content fragments (the figure contract and default stance, plus a per-backend quick-start for Python and R).
6	- A dynamic layer (this file plus `manifest.yaml`) that detects the plotting backend and loads only the fragment needed for the current job. The large design, API, pattern, and QA material lives in on-demand references.
7
8	Do not try to apply the figure logic from memory or from this router. Always load fragments from disk as described below.
9
10	## Routing protocol
11
12	Follow these five steps every time the skill is invoked.
13
14	### 1. Load the manifest and the core layer
15
16	Read [manifest.yaml](manifest.yaml). It declares the `backend` axis, the allowed values, and the file paths each value maps to.
17
18	Also read every file listed under `always_load` (`static/core/contract.md` and `static/core/stance.md`). These hold the figure contract, the backend gate, the missing-runtime rule, the privacy rule, and the default operating stance that apply to every figure job.
19
20	### 2. Resolve the backend — a blocking gate
21
22	Backend selection blocks everything else. Decide the `backend` value only from an explicit user choice or a clearly language-specific input file/workflow:
23
24	- `python` — matplotlib / seaborn.
25	- `r` — ggplot2 / patchwork / ComplexHeatmap.
26
27	If the user has not explicitly chosen, ask exactly one concise question — Python or R? — and stop. Do not default, guess, generate mock data, or write scripts before the answer. Only recommend a backend when the user explicitly asks you to choose; then use `references/backend-selection.md`, state the reason, and proceed. Once selected, the backend is exclusive for all drawing, previewing, exporting, and visual QA (see `core/contract.md`).
28
29	### 3. Load the matching backend fragment
30
31	After the backend is resolved, Read the mapped fragment (`static/fragments/backend/python.md` or `static/fragments/backend/r.md`). It carries the backend-only execution rule and the publication quick-start (rcParams/theme and export helper). Do not load the other backend's fragment.
32
33	### 4. Build the figure using the loaded material
34
35	Apply the loaded material in this order:
36
37	1. Figure contract (`core/contract.md`) — write the core conclusion, map the evidence chain, classify the archetype, set the journal/export contract, before any code.
38	2. Default stance (`core/stance.md`) — archetype-first composition, hero panel, restrained palette, statistics/integrity as part of the figure.
39	3. Backend fragment — the exclusive Python or R quick-start and execution rule.
40
41	The chart serves the scientific logic; aesthetic polish is subordinate to making the core conclusion clear, defensible, and reviewable.
42
43	### 5. Reach for references only when needed
44
45	The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest — for example `references/figure-contract.md` to build the contract, `references/api.md` for the Python palette and helpers, `references/r-workflow.md` for R, `references/design-theory.md` for color/typography/export rationale, `references/common-patterns.md` and `references/chart-types.md` for layout/chart recipes, `references/nature-2026-observations.md` for real Nature page archetypes, `references/qa-contract.md` before final delivery, and `references/tutorials.md` / `references/demos.md` for worked examples.
46
47	## Why this split
48
49	- The static layer is versioned and reviewable. The backend gate is now explicit in the manifest rather than buried in prose.
50	- The dynamic layer keeps each invocation cheap: only the selected backend's quick-start enters context, and the 2,600+ lines of reference depth load only when a step needs them.
51	- The router itself is short on purpose. Update fragments and refe

People who liked this also viewed

6 picks

Type