name: visual-asset-generator
Inherits all available tools
Additional assets for this skill
This skill inherits all available tools. When active, it can use any tool Claude has access to.
name: visual-asset-generator description: Automatically generate research diagrams, charts, tables, and visualizations from data or descriptions. Creates publication-ready visual assets including PRISMA flow diagrams, methodology flowcharts, results charts, comparison tables, and architecture diagrams. Use when preparing manuscripts, presentations, or documentation that requires professional visual elements. version: 1.0.0 category: research tags:
Automatically generate publication-ready visual assets (diagrams, charts, tables) from data or descriptions in seconds, filling the gap between text-based research and visual communication.
Activate this skill when:
DO NOT use this skill for:
This skill NEVER fabricates data.
This skill only visualizes:
input:
asset_type: enum[diagram, chart, table, specialized] (required)
subtype: string (required)
# For diagrams: "prisma", "methodology", "pipeline", "architecture", "conceptual"
# For charts: "bar", "line", "scatter", "box", "heatmap"
# For tables: "comparison", "summary", "feature_matrix", "literature"
# For specialized: "model_architecture", "ablation", "training_curves"
data: object | array | null
# Actual data to visualize (required for charts)
# NULL for structural diagrams (will generate template)
description: string (required for diagrams)
# Natural language description of what to visualize
style:
format: enum[svg, mermaid, graphviz, ascii, markdown] (default: mermaid)
color_scheme: enum[default, publication, presentation, minimal]
size: enum[small, medium, large, full_page]
output_preferences:
include_caption: boolean (default: true)
include_source_note: boolean (default: true)
latex_compatible: boolean (default: false)
output:
visual_asset:
type: string
subtype: string
format: string
content: string # The actual diagram/chart/table code
rendering:
code: string # Mermaid/GraphViz/Markdown code
preview_instructions: string
export_commands: array[string]
caption:
short: string
long: string
metadata:
data_source: string # "user_provided" | "template_placeholder"
generation_time: number
warnings: array[string]
Determine the appropriate visualization for the request:
## Asset Classification
**Request Analysis**:
- Type: [diagram | chart | table | specialized]
- Subtype: [specific type]
- Data Available: [yes | no | partial]
- Format: [mermaid | graphviz | markdown | ascii]
**Validation**:
- [ ] Data provided for data-dependent visualizations
- [ ] Description provided for structural diagrams
- [ ] Format supported for asset type
flowchart TD
subgraph Identification
A[Records identified through database searching\nn = YOUR_NUMBER]
B[Additional records from other sources\nn = YOUR_NUMBER]
end
subgraph Screening
C[Records after duplicates removed\nn = YOUR_NUMBER]
D[Records screened\nn = YOUR_NUMBER]
E[Records excluded\nn = YOUR_NUMBER]
end
subgraph Eligibility
F[Full-text articles assessed\nn = YOUR_NUMBER]
G[Full-text excluded with reasons\nn = YOUR_NUMBER]
end
subgraph Included
H[Studies included in qualitative synthesis\nn = YOUR_NUMBER]
I[Studies included in quantitative synthesis\nn = YOUR_NUMBER]
end
A --> C
B --> C
C --> D
D --> E
D --> F
F --> G
F --> H
H --> I
flowchart LR
subgraph Input
A[Data Collection]
end
subgraph Processing
B[Preprocessing]
C[Feature Extraction]
D[Model Training]
end
subgraph Output
E[Evaluation]
F[Results]
end
A --> B --> C --> D --> E --> F
| Method | Accuracy | Precision | Recall | F1-Score | Parameters |
|--------|----------|-----------|--------|----------|------------|
| Baseline | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] |
| Proposed | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] |
| SOTA | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] | [YOUR_DATA] |
*Table X: Performance comparison on [DATASET]. Best results in **bold**.*
flowchart TB
subgraph Encoder
E1[Input Layer]
E2[Conv Block 1]
E3[Conv Block 2]
E4[Bottleneck]
end
subgraph Decoder
D1[Upsample 1]
D2[Upsample 2]
D3[Output Layer]
end
E1 --> E2 --> E3 --> E4
E4 --> D1 --> D2 --> D3
E2 -.->|skip| D2
E3 -.->|skip| D1
For data-dependent visualizations:
## Data Integration
**Data Validation**:
- [ ] Data format matches visualization requirements
- [ ] No missing critical values
- [ ] Data types appropriate (numeric for charts)
**Data Transformation**:
1. Parse provided data
2. Validate data integrity
3. Transform to visualization format
4. Generate appropriate labels
**If Data Missing**:
- Generate template with [YOUR_DATA] placeholders
- Add warning: "Template generated - replace placeholders with actual data"
Generate the visualization code:
// Mermaid diagram generation
const generateMermaid = (type, data, description) => {
// Select template based on type
// Populate with data or placeholders
// Return mermaid code
};
digraph G {
rankdir=TB;
node [shape=box, style=filled, fillcolor=lightblue];
// Generated nodes and edges
}
| Column 1 | Column 2 | Column 3 |
|----------|----------|----------|
| Data 1 | Data 2 | Data 3 |
+----------------+ +----------------+
| Input | --> | Processing |
+----------------+ +----------------+
|
v
+----------------+
| Output |
+----------------+
Generate publication-ready captions:
## Caption Generation
**Short Caption** (for list of figures):
"Figure X: [Concise description of visualization]"
**Long Caption** (for figure):
"Figure X: [Detailed description including key findings,
methodology notes, and data sources].
[Specific observations].
Source: [Data attribution if applicable]."
Input:
asset_type: diagram
subtype: prisma
data:
identified: 1245
duplicates_removed: 890
screened: 890
excluded_screening: 650
full_text_assessed: 240
excluded_full_text: 192
qualitative: 48
quantitative: 32
Output:
flowchart TD
subgraph Identification
A[Records identified through database searching<br/>n = 1245]
end
subgraph Screening
C[Records after duplicates removed<br/>n = 890]
D[Records screened<br/>n = 890]
E[Records excluded<br/>n = 650]
end
subgraph Eligibility
F[Full-text articles assessed<br/>n = 240]
G[Full-text excluded with reasons<br/>n = 192]
end
subgraph Included
H[Studies in qualitative synthesis<br/>n = 48]
I[Studies in quantitative synthesis<br/>n = 32]
end
A --> C --> D
D --> E
D --> F
F --> G
F --> H --> I
Input:
asset_type: table
subtype: comparison
data:
methods:
- name: "Baseline CNN"
accuracy: 0.823
f1: 0.814
params: "2.3M"
- name: "Proposed Method"
accuracy: 0.891
f1: 0.887
params: "1.8M"
- name: "ResNet-50"
accuracy: 0.876
f1: 0.869
params: "25.6M"
Output:
| Method | Accuracy | F1-Score | Parameters |
|--------|----------|----------|------------|
| Baseline CNN | 0.823 | 0.814 | 2.3M |
| **Proposed Method** | **0.891** | **0.887** | **1.8M** |
| ResNet-50 | 0.876 | 0.869 | 25.6M |
*Table 1: Performance comparison on test dataset.
Best results highlighted in **bold**.
Proposed method achieves highest accuracy with fewest parameters.*
# Preview in VS Code with Mermaid extension
# Or use: https://mermaid.live/
# Export to SVG:
mmdc -i diagram.mmd -o diagram.svg
# Render to PNG:
dot -Tpng diagram.dot -o diagram.png
# Render to SVG:
dot -Tsvg diagram.dot -o diagram.svg
\begin{table}[h]
\centering
\caption{Performance Comparison}
\begin{tabular}{lccc}
\toprule
Method & Accuracy & F1 & Params \\
\midrule
Baseline & 0.823 & 0.814 & 2.3M \\
Proposed & \textbf{0.891} & \textbf{0.887} & \textbf{1.8M} \\
\bottomrule
\end{tabular}
\end{table}
Version: 1.0.0 Category: Research / Visualization Formats: Mermaid, GraphViz, Markdown, ASCII, LaTeX Design: Ethical visualization with placeholder-based data insertion