rtk

Compress NetScript command output to reduce AI token consumption.

Updated Jun 4, 2026
One-click install
npx skills add https://github.com/rickylabs/netscript --skill rtk-rickylabs
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rtk
Source: https://github.com/rickylabs/netscript/tree/main/.agents/skills/rtk
Command: npx skills add https://github.com/rickylabs/netscript --skill rtk-rickylabs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The rtk Skill reduces the amount of tokens consumed by certain NetScript commands, optimizing the use of AI resources for read-heavy operations.

Core Features & Use Cases

  • Token Reduction: Compresses output of commands like git, grep, ls, and docker to reduce token usage.
  • Use Case: When running a series of git log commands, rtk can significantly reduce the token consumption by compressing the output.

Quick Start

Prefix your commands with rtk to save tokens, e.g., rtk git status.

Frequently Asked Questions about rtk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce token consumption when running shell commands in NetScript workflows?

To reduce token consumption in NetScript workflows, prefix read-heavy shell commands like `git log` with the `rtk` proxy. This filters and compresses the command output, significantly lowering the AI tokens consumed without altering the command's semantics or exit code.

Does the token reduction proxy alter the exit code or semantics of Git and Docker commands?

No, the token reduction proxy does not alter the semantics or exit code of Git and Docker commands. It strictly filters and compresses the output text to save tokens, ensuring your command optimization process maintains the original command behavior.

How do I use a CLI proxy to compress output for read-heavy commands?

To compress output for read-heavy commands, simply prefix your original command with the proxy name, such as changing `git status` to `rtk git status`. This command optimization approach automatically filters and compresses the terminal output to reduce token usage.

When should I use command optimization for AI token reduction?

You should use command optimization for AI token reduction during read-heavy NetScript workflows, such as running a series of Git operations or Docker commands. It is specifically designed to compress the large output generated by these frequent read operations.

Can I use the token reduction proxy for write-heavy shell operations?

The token reduction proxy is suitable for read-heavy shell commands rather than write-heavy operations. It focuses on filtering and compressing the large output text from commands like `git`, `grep`, and `ls` to effectively reduce AI token consumption.