System Commander

Convert user tasks to optimal Linux/Python commands. Use when user needs file processing, data extraction, text manipulation, or any task that can be solved with system-level tools instead of AI inference.

When to Use

Activate this skill when:

• User asks for file processing, text manipulation, or data extraction
• Task can be solved with Linux/Python commands
• Goal is to minimize AI inference and maximize efficiency
• Keywords: "system command", "linux", "bash", "one-liner", "file processing"

Core Philosophy: System First, AI Last

Before any AI reasoning, try these in order:

1. Pure Linux tools - awk, sed, grep, cut, tr, sort, uniq
2. Linux + file tools - find, xargs, parallel, jq, csvkit
3. Python one-liners - Quick scripts for complex logic
4. AI subordinate - Only when above won't suffice

Command Patterns by Task Type

File Operations

Task	System Solution	AI Solution
List large files	find . -size +100M -ls	❌ Don't delegate
Count lines	wc -l file.txt	❌ Don't delegate
Search text	grep -r "pattern" .	❌ Don't delegate
Replace text	sed -i 's/old/new/g' file	❌ Don't delegate
Extract column	awk -F',' '{print $2}' file.csv	❌ Don't delegate

Data Processing

Task	System Solution	AI Solution
JSON query	jq '.key.subkey' file.json	❌ Don't delegate
CSV manipulation	csvcut -c 1,3 file.csv	❌ Don't delegate
Sort & unique	sort file uniq -c	❌ Don't delegate
Join files	join -t',' file1 file2	❌ Don't delegate

Text Processing

Task	System Solution	AI Solution
Line extraction	sed -n '5,10p' file	❌ Don't delegate
Word count	tr ' ' '\n' sort uniq -c	❌ Don't delegate
Format conversion	iconv -f UTF-8 -t ASCII	❌ Don't delegate

Response Format

When generating commands:

1. Provide the command (ready to copy-paste)
2. Explain what it does (brief)
3. Show expected output (example)
4. Note alternatives (if applicable)

Examples

Example 1: Extract Email Addresses

User: "Extract all email addresses from this log file"

System Commander Response:

bash

# Extract emails using grep with regex
grep -oE '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}' logfile.txt | sort -u

# What it does:
# - -o: output only matching parts
# - -E: extended regex
# - Sorts and removes duplicates

Example 2: Count Files by Extension

User: "Count how many files of each type are in this directory"

System Commander Response:

bash

# Count files by extension
find . -type f | sed 's/.*\.//' | tr '[:upper:]' '[:lower:]' | sort | uniq -c | sort -rn

# What it does:
# - Find all files
# - Extract extension (last . to end)
# - Normalize case
# - Count and sort by frequency

Example 3: Parse JSON Values

User: "Get all 'status' values from this JSON file"

System Commander Response:

bash

# Using jq (install with apt-get install jq)
jq -r '.[].status' data.json | sort | uniq -c

# Alternative using grep (if jq unavailable):
grep -oP '"status": "\K[^"]+' data.json | sort | uniq -c

Example 4: Batch Rename Files

User: "Rename all .txt files to .bak"

System Commander Response:

bash

# Dry run first (see what would happen)
ls *.txt | sed 's/\.txt$//' | xargs -I {} echo mv {}.txt {}.bak

# Execute if looks correct
ls *.txt | sed 's/\.txt$//' | xargs -I {} mv {}.txt {}.bak

# One-liner alternative:
for f in *.txt; do mv "$f" "${f%.txt}.bak"; done

Advanced Patterns

Parallel Processing

bash

# Process files in parallel (4 jobs)
find . -name '*.log' | xargs -P 4 -I {} grep 'ERROR' {}

# Using GNU parallel (apt-get install parallel)
find . -name '*.json' | parallel 'jq .name {}'

Complex Text Extraction

bash

# Extract text between markers
sed -n '/START/,/END/p' file.txt

# Multi-line pattern replacement
sed '/pattern/{n;s/old/new/}' file.txt

# Process only matching files
grep -l 'pattern' *.txt | xargs sed -i 's/old/new/g'

Data Transformation

bash

# CSV to JSON (requires csvkit)
csvjson data.csv > data.json

# JSON to CSV
jq -r '.[] | [.key1, .key2] | @csv' data.json > output.csv

# Column statistics
awk -F',' '{sum+=$3} END {print "Sum:", sum, "Avg:", sum/NR}' data.csv

Python One-Liners

When pure Linux isn't enough, use Python:

bash

# Complex JSON processing
python3 -c "
import json,sys
data=json.load(open('file.json'))
print([x['name'] for x in data if x['active']])
"

# Text processing with regex
python3 -c "
import re,sys
for line in sys.stdin:
    m=re.search(r'pattern', line)
    if m: print(m.group(1))
" < input.txt

When NOT to Use System Commands

Don't suggest system commands when:

• Task requires natural language understanding
• Contextual analysis of meaning
• Creative writing or content generation
• Complex multi-step reasoning
• Security-sensitive operations needing verification

Token Efficiency Rules

1. Never rewrite command output - Use §§include() instead
2. Prefer pipes over loops - | chains are more efficient
3. Use built-in tools - awk, sed vs Python imports
4. Batch operations - Process all files at once with xargs

Installation Prerequisites

Some commands need packages:

bash

# JSON processing
apt-get install jq

# CSV processing
apt-get install csvkit

# Parallel execution
apt-get install parallel

# Text processing
apt-get install silversearcher-ag  # ag command

Skill Integration

This skill works with:

• agent-orchestrator: System commands become subtask solutions
• a0-token-optimizer: Minimal tokens for maximum utility
• toon-adoption: Store command patterns in TOON format