Claude-skill-registry create-pdf-fixture

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/create-pdf-fixture" ~/.claude/skills/majiayu000-claude-skill-registry-create-pdf-fixture && rm -rf "$T"

manifest: skills/data/create-pdf-fixture/SKILL.md

create-pdf-fixture

Generate complete PDF test fixtures that combine:

Proper ReportLab tables via
```
create-table
```
(detectable by Marker/Camelot)
AI-generated images via
```
create-image
```
(diagrams, decorative elements)
Text content with various formatting challenges

Why This Exists

Creating test PDFs that properly exercise extractors requires:

Tables built with ReportLab (not raw drawing commands)
Images that test VLM classification (decorative vs data)
Edge cases: empty sections, malformed titles, nested structures

This skill orchestrates sibling skills for modular, reusable fixtures.

Quick Start

cd .pi/skills/create-pdf-fixture

# Generate the extractor bug reproduction fixture
uv run generate.py extractor-bugs --output test.pdf

# Generate a simple fixture
uv run generate.py simple --output simple_test.pdf

# List available presets
uv run generate.py list-presets

# Verify table detection
uv run generate.py verify test.pdf

Presets

Preset	Description	Tests
`extractor-bugs`	Reproduces known extractor issues	Empty sections, false tables, malformed titles
`simple`	Basic PDF with table and text	Basic extraction

Sibling Skills Used

Skill	Purpose
`create-table`	Creates ReportLab tables (Marker-detectable)
`create-image`	AI-generated images with caching

Cached images from

create-image/cached_images/

```
decorative.png
```
- Cover illustration
```
flowchart.png
```
- Process diagram
```
network_arch.png
```
- Architecture diagram

Legacy Usage (Still Supported)

# Via wrapper (uses extractor project)
./run.sh --example --name test_fixture
./run.sh --spec content_spec.json --name my_fixture

JSON Spec Format (Legacy)

{
  "style": "standard",
  "sections": [
    {
      "title": "1. Requirements",
      "level": 1,
      "content": [
        {"type": "text", "text": "This document describes requirements."},
        {"type": "table", "columns": ["ID", "Name"], "rows": [["1", "Alice"]]},
        {"type": "figure", "description": "Architecture diagram"}
      ]
    }
  ]
}

Output

extractor_bugs_fixture.pdf

- Cached in

cached_fixtures/

Custom output via
```
--output
```
flag

Dependencies

dependencies = [
    "pymupdf>=1.23.0",
    "reportlab>=4.0.0",
    "typer>=0.9.0",
    "pillow>=10.0.0",
]