Skim FAQs

Question 1

What is Skim and how does it optimize AI interactions?

Accepted Answer

Skim is a developer tool designed to optimize AI context. It automatically extracts only the essential structure (schema) from large command outputs (like API responses or logs), returning this concise data to AI agents instead of the full, verbose output. This saves tokens and keeps the AI focused.

Question 2

What happens to the full command output when Skim is used?

Accepted Answer

When Skim processes a command, the complete output is saved locally to temporary files. This allows AI agents to receive the schema for quick understanding, while the full data remains accessible for on-demand inspection using tools like `skim_drill` without flooding the AI's context window.

Question 3

Which data formats does Skim support for schema extraction?

Accepted Answer

Skim is versatile and supports schema extraction for a wide range of data formats. This includes structured data like JSON, CSV, YAML, XML/HTML, and it can also provide line counts and previews for plain text logs.

Question 4

How do I integrate and use Skim with AI agents like Claude Code?

Accepted Answer

Skim is designed as an MCP (Multi-Modal Code Provider) Server for Claude Code. You can easily install it via `git clone` and then add it to your Claude Code configuration. It provides simple commands like `skim_exec` to run commands, `skim_drill` to query saved data, `skim_list` for files, and `skim_clean` for cleanup.

Question 5

Can Skim help reduce token costs and improve AI efficiency?

Accepted Answer

Absolutely. By sending only the schema instead of raw data blobs, Skim significantly reduces the amount of text an AI agent needs to process. This directly translates to lower token usage, decreased costs, and more efficient, less distracted AI reasoning for developers.

Skim

Skim

Key Features

Use Cases

Key Features

Use Cases