pst-converter
Convert Microsoft Outlook Personal Storage Table (.pst) files into AI-friendly formats (Markdown, JSON, CSV). Use this skill to extract emails, metadata, and attachments from legacy email archives for analysis, context, or migration.
Datos de origen
- Repositorio
- nweii/convert-psts
- Última actividad en el origen
- 19 de diciembre de 2025 a las 17:51
- Idioma detectado de SKILL.md
- inglés
- Estrellas
- 1
- Forks
- 1
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SKILL.md
Instrucciones de origen · Vista previa de solo lectura- name
- pst-converter
- description
- Convert Microsoft Outlook Personal Storage Table (.pst) files into AI-friendly formats (Markdown, JSON, CSV). Use this skill to extract emails, metadata, and attachments from legacy email archives for analysis, context, or migration.
- allowed-tools
- ["run_terminal_cmd","read_file"]
# PST Converter Skill
## Description
This skill provides a tool to extract and format data from Outlook PST files. It is useful for:
- Reading legacy email archives.
- Converting PST content to Markdown for LLM context.
- Extracting metadata for analysis (CSV/JSON).
## Requirements
- **System**: `libpst` must be installed.
- macOS: `brew install libpst`
- Linux: `sudo apt-get install pst-utils`
- **Python**: Python 3.8+ (Standard library only).
## Instructions
Run the `cli.py` script found in this directory.
### Basic Syntax
```bash
python3 cli.py <path_to_pst_file> [options]
```
### Options
- `-f, --format`: Output format. Choices: `markdown` (default), `json`, `csv`, `both` (md+json), `all`.
- `--full`: Include full email bodies (default is metadata-only).
- `--folders`: Preserve original folder structure.
- `--include-threading`: Include thread ID metadata.
- `-o, --output <dir>`: Specify output directory (default: `./output`).
## Examples
### 1. Quick Summary (Metadata only)
Good for scanning an archive's contents.
```bash
python3 cli.py archive.pst
```
### 2. Prepare for LLM Context (Markdown)
Extracts full content into a readable Markdown format.
```bash
python3 cli.py archive.pst --full -f markdown
```
### 3. Data Analysis (JSON/CSV)
Extract structured data.
```bash
python3 cli.py archive.pst --full -f json
```
## Troubleshooting
- **`readpst` not found**: Install `libpst` via your system package manager.
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