--- frontmattername: data-processor
description: Data processing skill with Python and shell scripts for file analysis and transformation
version: 1.0.0
author: XSpoonAi Team
tags:
- data
- processing
- analysis
- scripts
triggers:
- type: keyword
keywords:
- process
- analyze
- transform
- data
- parse
- convert
priority: 80
- type: pattern
patterns:
- "(?i)(process|analyze|transform) .*(data|file|json|csv)"
- "(?i)convert .* to .*"
priority: 75
parameters:
- name: input
type: string
required: false
description: Input data or file path to process
- name: format
type: string
required: false
default: json
description: Output format (json, csv, text)
composable: true
persist_state: false
scripts:
enabled: true
working_directory: ./scripts
definitions:
- name: analyze
description: Analyze input data and provide statistics
type: python
file: analyze.py
timeout: 30
- name: transform
description: Transform data format
type: python
file: transform.py
timeout: 30
- name: setup
description: Initialize processing environment
type: bash
inline: |
echo "Initializing data processor environment..."
echo "Ready for processing"
run_on_activation: true
- name: cleanup
description: Clean up temporary files
type: bash
inline: |
echo "Cleaning up temporary files..."
echo "Cleanup complete"
run_on_deactivation: trueData Processor Skill
You are now operating in Data Processing Mode. You have access to scripts that can help process and analyze data.
Available Scripts
analyze
Analyzes input data and provides statistics. Pass data via stdin.
Usage: The AI will call this script when you need to analyze data structures, get statistics, or understand data patterns.
transform
Transforms data between formats. Supports JSON, CSV, and text.
Usage: The AI will call this script when you need to convert data between different formats.
setup (Activation Script)
Runs automatically when this skill is activated to prepare the processing environment.
cleanup (Deactivation Script)
Runs automatically when this skill is deactivated to clean up temporary files.
Guidelines
- •Always validate input before processing
- •Handle errors gracefully and provide informative messages
- •Preserve data integrity during transformations
- •Report statistics when analyzing data
Example Tasks
- •"Analyze this JSON data and tell me about its structure"
- •"Convert this CSV to JSON format"
- •"Process this log file and extract key metrics"