create-pdf-fixture
Create complete PDF test fixtures combining ReportLab tables and AI-generated images. Orchestrates create-table and create-image skills. Creates PDFs designed to test/expose extractor bugs.
소스 정보
- 저장소
- grahama1970/agent-stack-public
- 최근 소스 활동
- 2026년 9월 24일 15:51
- 감지된 SKILL.md 언어
- 영어
- 스타
- 0
- 포크
- 0
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
파일 탐색기
5 개 파일SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- create-pdf-fixture
- description
- Create complete PDF test fixtures combining ReportLab tables and AI-generated images. Orchestrates create-table and create-image skills. Creates PDFs designed to test/expose extractor bugs.
- allowed-tools
- Bash, Read, Write
- triggers
- ["create pdf fixture","create test pdf","generate pdf fixture","make test pdf","pdf for testing","extractor test fixture","bug reproduction pdf"]
- metadata
- {"short-description":"Create PDF test fixtures (tables + images)"}
- provides
- ["create-pdf-fixture"]
- composes
- ["task-monitor","agentic-evals"]
- disciplines
- ["extraction","evaluation-quality"]
# 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:
1. Tables built with ReportLab (not raw drawing commands)
2. Images that test VLM classification (decorative vs data)
3. Edge cases: empty sections, malformed titles, nested structures
This skill orchestrates sibling skills for modular, reusable fixtures.
## Quick Start
```bash
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)
```bash
# Via wrapper (uses extractor project)
./run.sh --example --name test_fixture
./run.sh --spec content_spec.json --name my_fixture
```
## JSON Spec Format (Legacy)
```json
{
"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
```toml
dependencies = [
"pymupdf>=1.23.0",
"reportlab>=4.0.0",
"typer>=0.9.0",
"pillow>=10.0.0",
]
```
GitHub에서 보기