---
name: pdf-generation-troubleshooting-5884188e4bba
description: Systematic fallback workflow for PDF generation through pandoc, reportlab, and fpdf2 with installation verification
---

# PDF Generation Troubleshooting Workflow

This skill provides a systematic approach to generating PDFs when multiple tools may be unavailable. Follow this fallback sequence to ensure PDF generation succeeds.

## Workflow Overview

1. **Try pandoc first** (simplest for markdown/HTML conversion)
2. **Fallback to reportlab** (Python library for programmatic PDFs)
3. **Fallback to fpdf2** (alternative Python PDF library)

Each step includes installation verification before execution.

## Step 1: Attempt pandoc Conversion

Use pandoc for markdown or HTML to PDF conversion. Check availability first:

```bash
# Check if pandoc is available
which pandoc || echo "pandoc not found"
```

If available, convert:

```bash
pandoc input.md -o output.pdf
```

If pandoc fails or is unavailable, proceed to Step 2.

## Step 2: Attempt reportlab

### Check Installation

```bash
python3 -c "import reportlab" 2>/dev/null && echo "reportlab available" || echo "reportlab not found"
```

### Install if Needed

```bash
pip install reportlab
```

### Create PDF Script

Use `write_file` to create a Python script:

```python
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

def create_pdf(filename, content):
    c = canvas.Canvas(filename, pagesize=letter)
    c.drawString(100, 750, content)
    c.save()

if __name__ == "__main__":
    create_pdf("output.pdf", "Your content here")
```

### Execute Script

Use `run_shell` with proper directory context:

```bash
cd /path/to/working/directory && python3 script.py
```

If reportlab fails, proceed to Step 3.

## Step 3: Attempt fpdf2

### Check Installation

```bash
python3 -c "from fpdf import FPDF" 2>/dev/null && echo "fpdf2 available" || echo "fpdf2 not found"
```

### Install if Needed

```bash
pip install fpdf2
```

### Create PDF Script

```python
from fpdf import FPDF

def create_pdf(filename, text):
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size=12)
    pdf.cell(200, 10, txt=text, ln=True)
    pdf.output(filename)

if __name__ == "__main__":
    create_pdf("output.pdf", "Your content here")
```

### Execute Script

```bash
cd /path/to/working/directory && python3 script.py
```

## Decision Matrix

| Tool | Best For | Limitations |
|------|----------|-------------|
| pandoc | Markdown/HTML conversion | Requires external installation |
| reportlab | Complex layouts, graphics | Steeper learning curve |
| fpdf2 | Simple text PDFs | Limited formatting options |

## Error Handling Pattern

For each tool attempt:

1. Check availability/installation
2. Install if missing (`pip install <package>`)
3. Create script using `write_file`
4. Execute using `run_shell` with `cd <dir> && <command>`
5. Verify output file exists
6. If fails, move to next tool in sequence

## Example Fallback Implementation

```bash
# Pseudocode for full workflow
if command -v pandoc >/dev/null 2>&1; then
    pandoc input.md -o output.pdf && exit 0
fi

if python3 -c "import reportlab" 2>/dev/null; then
    # Create and run reportlab script
    exit 0
fi

# Final fallback: fpdf2
pip install fpdf2
# Create and run fpdf2 script
```

## Key Principles

- **Always verify** tool availability before attempting use
- **Install on-demand** when a tool is missing
- **Use write_file** for script creation (ensures clean, versionable code)
- **Use run_shell** with explicit directory context (`cd <dir> && <cmd>`)
- **Progressive fallback** ensures at least one method succeeds
- **Verify output** after each attempt before moving to next tool

---
Source attribution: AG064
Original project: https://github.com/AG064/OpenSpace/blob/ff671ef61ed6587c49bd54c81cdc751c0b99e363/gdpval_bench/skills/pdf-generation-troubleshooting/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 ✨Data Intelligence Lab@HKU✨

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: AG064
Original project: https://github.com/AG064/OpenSpace/blob/ff671ef61ed6587c49bd54c81cdc751c0b99e363/gdpval_bench/skills/pdf-generation-troubleshooting/SKILL.md
Attribution basis: Source repository record

Fields of work: Content & Media, Development & Engineering
Roles: Backend Developer, Data Engineer, Technical Writer
Specialties: Backend
Tools: Fpdf2, Pandoc, Reportlab
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 89cfd79cdc53f745cbcdb3037f933a6c2f431935b9c6f760a50ae34c99d677c4