File Compaction
Minimizes token usage in files while preserving their complete semantic meaning for AI consumption.
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Key features
- Preserves critical information like frontmatter, links, key facts, and code logic.
- Aggressively removes redundancy, filler words, and verbose explanations.
- Includes a workflow to measure and report token savings after compaction.
- Simplifies markdown and code blocks, removing decorative formatting and redundant examples.
- Employs a concise, information-dense writing style optimized for AI consumption.
Use cases
- Reducing the size of documentation before including it in a prompt for an AI model.
- Minimizing the token count of context files to fit within an AI's context window.
- Preparing large text files for analysis or summarization by language models to lower costs.
FAQ
How does this skill improve my workflow?
It automates the tedious task of manually shortening files. This allows you to process larger amounts of data more efficiently, lower your operational costs, and get more comprehensive results from Claude in a single interaction.
When should I use this skill?
Use this skill when you need to fit large documents or codebases into Claude's context window, reduce API costs for AI tasks, or speed up processing times for analysis, review, or summarization.
What does the File Compaction skill do?
The File Compaction skill intelligently rewrites files to use the fewest possible tokens while preserving their complete semantic meaning. It removes redundancy, verbose explanations, and decorative formatting, making content ideal for AI consumption.
What key capabilities does it provide?
This skill provides a complete workflow that preserves critical data like frontmatter and code logic, simplifies markdown, removes filler content, and reports on the exact token savings achieved after compaction.
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