Use when you have a written implementation plan to execute in a separate session with review checkpoints
npx skills add grahama1970/agent-skills --skill "fixture-image"
Install specific skill from multi-skill repository
# Description
>
# SKILL.md
name: fixture-image
description: >
Generate images for PDF test fixtures using HuggingFace FLUX.1-schnell (FREE).
Supports AI generation, mermaid diagrams, and placeholder images.
allowed-tools: Bash, Read, Write
triggers:
- generate fixture image
- create test image
- fixture image
- generate diagram
- create flowchart image
metadata:
short-description: AI-generated images for PDF test fixtures (HuggingFace FLUX - FREE)
Fixture Image Skill
Generate images for PDF extraction test fixtures using FREE AI image generation.
Features
- Ollama (local) - Z-Image Turbo or FLUX2-Klein via Ollama (FREE, no internet)
- FLUX.1-schnell - AI-generated images via HuggingFace (FREE remote)
- Mermaid diagrams - Flowcharts and architecture diagrams (FREE)
- Placeholder images - Random grayscale from picsum.photos (FREE)
- Solid color - Gray box with text label (always works)
- Size control - Specify dimensions for PDF embedding (auto-resized)
Quick Start
cd .pi/skills/fixture-image
# Generate an AI image (uses FLUX.1-schnell)
uv run --script generate.py "hardware verification flowchart for microprocessor" \
--output test_figure.png \
--size 400x600
# Generate with specific backend
uv run --script generate.py "network security architecture" \
--output security_arch.png \
--size 800x600 \
--backend flux
# Use placeholder fallback
uv run --script generate.py "placeholder" \
--output placeholder.png \
--size 400x300 \
--backend placeholder
Commands
generate - Create an image
uv run --script generate.py "<prompt>" [options]
Arguments:
| Argument | Description |
|----------|-------------|
| prompt | Description of the image to generate |
Options:
| Option | Short | Description | Default |
|--------|-------|-------------|---------|
| --output | -o | Output file path | fixture_image.png |
| --size | -s | Image dimensions (WxH) | 512x512 |
| --backend | -b | Generation backend | auto |
Backends
| Backend | Description | Requires | Cost |
|---|---|---|---|
ollama |
Z-Image/FLUX2 local generation | Ollama + model | FREE (local) |
flux |
FLUX.1-schnell AI generation | HF_TOKEN |
FREE (remote) |
mermaid |
Flowchart/diagram generation | mmdc CLI |
FREE |
placeholder |
picsum.photos (grayscale) | Nothing | FREE |
solid |
Gray box with text label | Pillow | FREE |
auto |
Try backends in order | Any available | - |
Setup
Option 1: Ollama (macOS only - MLX framework)
Note: Ollama image generation currently only works on macOS (Apple Silicon). Linux/NVIDIA support is "coming soon" per Ollama docs.
# macOS only
ollama pull x/z-image-turbo
# or
ollama pull x/flux2-klein
Option 2: HuggingFace Token (FREE Remote)
Get a FREE HuggingFace token from huggingface.co/settings/tokens:
export HF_TOKEN="hf_your_token_here"
Option 3: Mermaid (for Diagrams)
npm install -g @mermaid-js/mermaid-cli
Example Prompts for Test Fixtures
Security Documents
"APT attack kill chain diagram with reconnaissance, weaponization, delivery, exploitation phases"
"network intrusion detection system architecture"
"malware analysis workflow flowchart"
Engineering Documents
"hardware verification flow for microprocessor with RTL, synthesis, and timing analysis"
"FPGA design pipeline from HDL to bitstream"
"embedded systems boot sequence diagram"
Scientific Documents
"machine learning pipeline with data preprocessing, training, and inference stages"
"experimental methodology flowchart"
"system architecture diagram with numbered components"
Cached Images (Reuse Before Generating)
Pre-generated images are available in cached_images/ - use these first to avoid unnecessary API calls:
| File | Description | Size |
|---|---|---|
decorative.png |
Abstract cover/decorative illustration | 512x512 |
flowchart.png |
Technical workflow/process diagram | 512x512 |
network_arch.png |
Network/system architecture diagram | 512x512 |
test_fixture.pdf |
12-page PDF with all image types embedded | 1.8MB |
# Copy cached image instead of generating
cp cached_images/flowchart.png /path/to/output.png
# Use pre-built test fixture for extractor testing
cp cached_images/test_fixture.pdf /path/to/test.pdf
Integration with PDF Generation
After generating images, embed them in synthetic PDFs:
import fitz # PyMuPDF
doc = fitz.open()
page = doc.new_page()
# Insert generated image
img_rect = fitz.Rect(50, 200, 450, 500) # x0, y0, x1, y1
page.insert_image(img_rect, filename="test_figure.png")
doc.save("fixture_with_figure.pdf")
Dependencies
dependencies = [
"huggingface_hub>=0.26.0",
"httpx",
"typer",
"pillow",
]
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.