Infografik

Infographic Skill

Creates professional infographics as PNG files via the Hugging Face Inference API (free, no billing required).

Philosophy: Data only becomes understandable when told visually. A good infographic reduces complexity – it doesn't add to it.

What This Skill Does

1. Asks for style and type – Technical/Professional or Creative/Visual via AskUserQuestion
2. Clarifies topic and data – User data or example data from references/beispieldaten.md
3. Selects color palette – From references/farbpaletten.md matching the style
4. Formulates image prompt – Detailed English prompt from data, style, and palette
5. Calls Hugging Face API – Generates PNG via FLUX.1-schnell or fallback model
6. Saves and presents – PNG with timestamp in project root

How to Use

Create an infographic with the current KPIs

Visualize the architecture of my project as a poster

Make an overview of the sprint results as an image

Prerequisites

The user needs a free Hugging Face account and an access token:

• Create token: https://huggingface.co/settings/tokens (Read access is sufficient)
• Set token as environment variable: export HF_TOKEN=hf_...

Instructions

Step 1 – Style query

The graphic style determines layout, color palette, and detail level of the image prompt. Without this decision, the prompt would be too generic – therefore always ask first with AskUserQuestion.

Question 1 – Graphic style (audience)

What graphic style do you want?

Options:

• Technical / Professional – For developers, architects, business analysts. Precise tiles, metrics, tables, structured layouts. Example: KPI dashboard, architecture overview, API documentation.
• Creative / Visual – For non-technical people, management, stakeholders, marketing. Large illustrations, colorful graphics, storytelling layouts. Example: Roadmap poster, process flow with symbols, team overview.

Question 2 – Infographic type

For Technical / Professional:

For Creative / Visual:

Step 2 – Clarify topic and data

Use user data or example data from references/beispieldaten.md.

Step 3 – Select color palette

Load references/farbpaletten.md; use color description for the prompt.

Step 4 – Formulate image prompt

The prompt must be in English and very detailed. Structure:

A professional [style] infographic about [topic].
Layout: [describe layout - grid, flow, poster, etc.]
Content: [list the key data points, labels, values]
Color scheme: [describe colors from palette]
Typography: [clean, bold titles, readable labels]
Style: flat design, high contrast, white background, no gradients, crisp edges.
Format: portrait orientation, 1024x1536 pixels.

Example prompt (Technical / KPI Dashboard):

A professional corporate KPI dashboard infographic. Clean grid layout with 6 metric tiles.
Content: Revenue 12.4M EUR (up 18%), Active Users 87,200, Error Rate 0.3%,
Uptime 99.9%, Sprint Velocity 42 points, NPS Score 72.
Color scheme: white background, cobalt blue (#1A56DB) headers,
emerald green (#0E9F6E) for positive KPIs, amber (#E3A008) for warnings.
Typography: bold sans-serif titles, monospace values.
Style: flat design, no shadows, card-based layout, horizontal dividers.
Format: portrait, 1024x1536.

Example prompt (Creative / Storytelling Poster):

A vibrant storytelling infographic poster about digital transformation.
Layout: top-to-bottom flow with 4 illustrated steps connected by arrows.
Content: Step 1 Analysis (magnifying glass icon), Step 2 Design (pencil icon),
Step 3 Build (gear icon), Step 4 Launch (rocket icon).
Color scheme: mint-white background (#FAFFFE), teal (#0D9488) primary,
indigo (#4F46E5) accent, orange (#F97316) highlights.
Typography: large bold step numbers, readable sans-serif descriptions.
Style: modern flat illustration, rounded icons, generous whitespace.
Format: portrait poster, 1024x1536.

Step 5 – Call API

Recommended model: black-forest-labs/FLUX.1-schnell (free, fast, high quality)

curl -s \
  -H "Authorization: Bearer $HF_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"inputs": "YOUR_PROMPT_HERE"}' \
  "https://router.huggingface.co/hf-inference/models/black-forest-labs/FLUX.1-schnell" \
  --output "infographic_$(date +%Y%m%d_%H%M%S).png"

Fallback model if FLUX is unavailable: stabilityai/stable-diffusion-xl-base-1.0

curl -s \
  -H "Authorization: Bearer $HF_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"inputs": "YOUR_PROMPT_HERE"}' \
  "https://router.huggingface.co/hf-inference/models/stabilityai/stable-diffusion-xl-base-1.0" \
  --output "infographic_$(date +%Y%m%d_%H%M%S).png"

Error handling

• 503 / Model loading: Model is still starting – wait 20 seconds, then retry
• 401 Unauthorized: HF_TOKEN missing or invalid
• Empty/corrupt PNG: Response was JSON error – cat infographic.png to diagnose
• Text in image unreadable: Known FLUX limitation – keep labels in prompt shorter, use only keywords

Step 6 – Save output and present

Save PNG to project root, then share with present_files.

Filename: Never overwrite an existing infographic. Always save with timestamp or descriptive name:

# Filename with timestamp
infographic_$(date +%Y%m%d_%H%M%S).png

# Or descriptive name
infographic_spring-architecture.png
infographic_kpi-dashboard.png

Check before saving whether a file with the planned name already exists.

Quality checklist

Check before presenting:

• Style query was performed (AskUserQuestion)
• Prompt is in English and contains all relevant data
• Color palette is described in the prompt
• PNG file was saved successfully (file size > 10 KB)
• File is in project root

References

Conventions

• Prompt language: English (Hugging Face models understand English best)
• File format: PNG, Portrait 1024x1536
• Filename: infographic_<description-or-timestamp>.png – never overwrite
• Style: Flat design, high contrast, no shadows/gradients
• Quality: Keep labels short – FLUX limitation with long texts