Which commands are supported by OKTK?

It has built-in support for git, docker, kubectl, npm, ls, curl, and grep, and it can automatically learn patterns for other custom commands.

Will OKTK break my terminal or scripts?

No, OKTK includes a safety fallback mechanism that returns the original raw output if it fails to apply a specialized filter or if the compression process fails.

How much money can I save with OKTK?

Users typically see a 60-90% reduction in token usage for CLI commands, which directly translates to significant savings on AI API billing.

Does OKTK remove important information from the AI?

No, OKTK uses specialized filters designed to retain critical data like branch names, error messages, and status codes while stripping away repetitive headers and filler text.

OKTK Token Optimizer

Name: OKTK Token Optimizer
Author: dvcrn

bydvcrn

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Productivity & Workflow

Optimizes LLM token usage by compressing verbose CLI command outputs from Git, Docker, and Kubectl before AI processing.

OKTK is a specialized utility designed to reduce AI API costs by up to 90% by intelligently filtering and compressing command-line outputs. By intercepting results from tools like Git, NPM, and Docker, it extracts only the essential information needed by the LLM, preventing context window bloat and unnecessary expenses without losing the critical context required for the AI to perform its task. Whether you are analyzing large log files or checking repository statuses, OKTK ensures that your AI assistant receives a dense, information-rich summary rather than thousands of lines of redundant formatting.

Key Features

01Significant token savings of 60-90% per CLI-heavy interaction

02Intelligent compression for Git, Docker, Kubectl, and NPM outputs

033 GitHub stars

04Automatic AI pattern learning for unsupported command types

05Built-in savings analytics to track total tokens and costs saved

06Fallback safety mechanism that preserves raw output if filtering fails

Use Cases

01Reducing API costs when using AI coding assistants for large repository operations

02Managing long Docker or Kubernetes logs within limited context windows

03Summarizing extensive test suite results for faster AI debugging

Key Features

01Significant token savings of 60-90% per CLI-heavy interaction

02Intelligent compression for Git, Docker, Kubectl, and NPM outputs

033 GitHub stars

04Automatic AI pattern learning for unsupported command types

05Built-in savings analytics to track total tokens and costs saved

06Fallback safety mechanism that preserves raw output if filtering fails

Use Cases

01Reducing API costs when using AI coding assistants for large repository operations

02Managing long Docker or Kubernetes logs within limited context windows

03Summarizing extensive test suite results for faster AI debugging