A high-efficiency toolkit for processing, transforming, and analyzing CSV, TSV, and JSON data using standard Python and CLI utilities.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install csv-pipeline
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install csv-pipeline using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is CSV Data Pipeline?
The CSV Data Pipeline is an essential component of the Openclaw Skills ecosystem, designed to handle complex tabular data operations with minimal overhead. It enables developers to perform extract, transform, and load (ETL) workflows directly on raw data files, supporting formats ranging from standard CSV to streamable JSON Lines.
This skill provides a bridge between raw data ingestion and actionable insights, making it a cornerstone for any automated data workflow. By utilizing these Openclaw Skills, users can bypass heavy database setups for quick analysis, format conversion, and reporting tasks using lightweight Python and shell scripts.
CSV Data Pipeline Use Cases
- Analyzing, filtering, or grouping tabular data provided in CSV, TSV, or JSON formats.
- Converting datasets between different formats such as CSV to JSON or JSON Lines to CSV.
- Cleaning and deduplicating messy datasets by normalizing whitespace and validating data types.
- Generating comprehensive summary reports in Markdown format for stakeholders.
- Performing complex joins between multiple datasets without requiring an external SQL database.
How CSV Data Pipeline Works
- The skill identifies the input file format and selects the appropriate tool, such as awk for quick filters or Python for complex logic.
- Data is parsed into a structured format, typically a list of dictionaries, to facilitate manipulation.
- Transformations like column renaming, type conversion, or calculated fields are applied to each record.
- If necessary, the data is grouped or joined with secondary datasets to enrich the information.
- The final processed data is written to a new file or summarized into a report based on the specific Openclaw Skills command used.
CSV Data Pipeline Setup
To get started with these Openclaw Skills, ensure you have Python 3 installed on your system. No external packages are required as it utilizes the standard library.
# Verify Python installation
python3 --version
# Example: Preview headers of a CSV file
head -1 data.csv
# Example: Filter a CSV file using awk
awk -F',' 'NR==1 || $3 > 100' data.csv > filtered.csv
CSV Data Pipeline Data Schema & Taxonomy
The pipeline organizes data into a row-based taxonomy, supporting various delimiters and structures. It treats the first row of CSV/TSV files as headers by default.
| Feature | Description |
|---|---|
| Input Formats | CSV, TSV, JSON, JSON Lines (JSONL) |
| Internal Model | List of Dictionaries (Column Name -> Value) |
| Output Formats | CSV, JSON, Markdown Reports |
| Data Cleaning | Automatic whitespace stripping and null normalization |
| Validation | Schema-based checks for ints, floats, dates, and emails |
CSV Data Pipeline Advanced Features
- Streaming processing capability for handling massive files that exceed system memory limits.
- Built-in SQLite integration for performing complex SQL queries on CSV files directly in-memory.
- Advanced data validation against custom schemas to ensure data integrity during ETL.
- Automated Markdown report generation including aggregates like sum, average, min, and max.
- Seamless multi-format conversion hooks to integrate with other Openclaw Skills in a larger automation chain.
SKILL.md
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