agentCLAWHUBUnverified
nature-figure
Generate publication-quality figures for Nature-series journals using Python (matplotlib) or R (ggplot2). Trigger when user wants to create, polish, or redes... Skill: nature-figure Owner: yang1bai Summary: Generate publication-quality figures for Nature-series journals using Python (matplotlib) or R (ggplot2). Trigger when user wants to create, polish, or redes... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-05-17T20:30:55.560Z | user Part of nature-paper-hub v1.0.0 Archive index: Archive v1.0.0: 3 files, 5144 bytes Files: skill-card.md (1886b), SKILL.md (7618b), _meta
OpenClaw
Rank
62
Safety
84
Downloads
1.8k
Updated
Oct 10, 2026
Version
1.0.0
Source
CLAWHUB
About
What it does, and when to use it.
Capability contract not published. No trust telemetry is available yet. 1.8K downloads reported by the source. Last updated 10/10/2026.
Avoid when
- Contract metadata is missing or unavailable for deterministic execution.
Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing
Public facts
Every fact links back to the source it came from.
- Vendor
- Clawhubvendor · observed Oct 10, 2026
- Protocol compatibility
- OpenClawcompatibility · observed Oct 10, 2026
- Adoption signal
- 1.8K downloadsadoption · observed Oct 10, 2026
- Latest release
- 1.0.0release · observed May 17, 2026
- Handshake status
- UNKNOWNsecurity
Install and run
Setup complexity: low.
clawhub skill install s17a5t9np755jt96j5sjz953dh86xqbw:nature-figure- Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
- Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Contract: missing
curl -s "https://www.xpersona.co/api/v1/agents/clawhub-yang1bai-nature-figure/snapshot"
Documentation
CLAWHUB
10,127 characters of source documentation, loaded on request.
Extracted files
3 files captured from the source.
SKILL.md
---
name: nature-figure
description: Generate publication-quality figures for Nature-series journals using Python (matplotlib) or R (ggplot2). Trigger when user wants to create, polish, or redesign scientific figures for high-impact journals. Handles multi-panel layouts, Nature color palettes, correct typography, and exports SVG/PDF/PNG.
---
# nature-figure
## Purpose
Generate multi-panel scientific figures that meet Nature portfolio visual standards:
correct typography, semantic colour palette, accessible design, and editable SVG output.
---
## Trigger Conditions
Activate when user mentions:
- "画图" / "figure" / "plot" / "科研绘图"
- "Nature figure" / "publication figure" / "publication plot"
- "matplotlib" / "ggplot" / "seaborn"
- "配色" / "color palette" / "color scheme"
- Wants to improve or reformat an existing figure
---
## Nature Figure Standards
### Typography
- Font family: **Arial** or **Helvetica** (sans-serif, never Times New Roman in figures)
- Minimum font size in final print: **7 pt** (axis labels, tick labels)
- Panel labels (a, b, c...): **8 pt bold**, lowercase
- Figure title (if any): not embedded in figure — goes in legend
- All text must be editable (not rasterized)
### Size & Resolution
| Format | Width | Resolution |
|--------|-------|------------|
| Single column | 89 mm (3.5 in) | 300 DPI min |
| 1.5 column | 120 mm (4.7 in) | 300 DPI min |
| Double column | 183 mm (7.2 in) | 300 DPI min |
| Line art | any | **600 DPI** |
| Final submission | PDF or TIFF | vector preferred |
### Colour Palette (Nature-approved, colorblind-safe)
```python
NATURE_COLORS = {
"blue": "#4878CF",
"red": "#D65F5F",
"green": "#6ACC65",
"orange": "#EE854A",
"purple": "#956CB4",
"teal": "#82C6E2",
"brown": "#D5BB67",
"gray": "#8C8C8C",
# Colorblind-safe primary pair:
"cb_blue": "#0072B2",
"cb_orange":"#E69F00",
}
```
- Never use pure red + green together (colorblind conflict)
- Use filled symbols + different shapes for accessibility, not colour alone
- Grayscale must remain distinguishable
### Panel Architecture
- Each panel makes **one clear point**
- Panel (a): overview / schematic / representative image
- Panels (b–d): quantitative evidence
- Final panel: comparison or generalizability
- Panels are labelled **a, b, c** (lowercase bold, top-left corner)
- White background; minimal gridlines (light gray, 0.5pt)
- No chartjunk: remove top and right spines
### Statistical Annotations
- Error bars: always define in legend (mean ± s.d. or ± s.e.m.)
- Significance: *, **, ***, **** for p < 0.05, 0.01, 0.001, 0.0001; prefer exact p-values
- n must be stated (e.g., n = 5 independent experiments)
- Box plots: show median, IQR, whiskers to 1.5×IQR, individual points overlaid
---
## Workflow
### Step 0: Auto-figure from data file (fastest path)
If user provides a CSV, Excel, or JSON data file:
```bash
python3 ~/.openclaw/workspace/skills/nature-paper-hub/scripts/auto_figure.py \
--inpu_meta.json
{
"ownerId": "kn7e8szja8rxwkwrchdswcj0d186wsdw",
"slug": "nature-figure",
"version": "1.0.0",
"publishedAt": 1779049855560
}skill-card.md
## Description: Generate publication-quality figures for Nature-series journals using Python (matplotlib) or R (ggplot2). This skill is ready for commercial/non-commercial use. ## Publisher: [yang1bai](https://clawhub.ai/user/yang1bai) ### License/Terms of Use: MIT-0 ## Use Case: Developers, researchers, and scientific authors use this skill to create, polish, or redesign Nature-style multi-panel figures and accompanying figure legends from supplied data or plotting requirements. ### Deployment Geography for Use: Global ## Known Risks and Mitigations: Risk: The auto-figure command template can run unintended shell commands when given an untrusted or unusual file path. Mitigation: Use only trusted, normalized input paths, verify the referenced helper script is present and trusted, and avoid interpolating user-controlled paths into shell commands. Risk: Generated plotting code or commands may be executed with insufficient argument validation. Mitigation: Prefer reviewing and running generated Python or R code with explicitly validated arguments before execution. ## Reference(s): - [BioRender](https://biorender.com) ## Skill Output: **Output Type(s):** [Code, Shell commands, Guidance, Markdown] **Output Format:** [Markdown with Python, R, or shell code blocks plus figure legend text and checklist items] **Output Parameters:** [1D] **Other Properties Related to Output:** [May include runnable matplotlib or ggplot2 code, export instructions for PDF/PNG outputs, and a pre-submission figure verification checklist.] ## Skill Version(s): 1.0.0 (source: server release metadata) ## Ethical Considerations: Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
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Machine-readable data
The same record, as JSON, for agents and crawlers.
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"label": "Adoption signal",
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"confidence": "medium",
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{
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"isPublic": true
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"sourceUrl": "https://clawhub.ai/yang1bai/nature-figure",
"sourceType": "release",
"confidence": "medium",
"observedAt": "2026-05-17T20:30:55.560Z",
"isPublic": true
}
]
}Record generated Oct 10, 2026.