What formats are available?

The skill currently supports table-based, bullet-points, yaml-structured, html-structured, genui, ultra-concise, and markdown-focused styles.

How does the Output Style Selector choose a format?

The skill analyzes keywords and the specific nature of your task to infer whether a table, list, or structured data block like YAML would be the most efficient way to present the information.

Does this skill increase my token usage?

On the contrary, its primary goal is to save tokens. By choosing concise formats like YAML or ultra-concise bullets, it reduces the word count of Claude's responses while keeping the data high-quality.

How do I disable the style selector for a single prompt?

You can temporarily disable the skill's behavior by including [style: off] in your message to Claude.

Can I manually force a specific style?

Yes, you can override the automatic selection at any time by adding a tag like [style: table] or [style: yaml] to your prompt.

Output Style Selector

Name: Output Style Selector
Author: MacroMan5

byMacroMan5

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Productividad y Flujo de Trabajo

Optimizes Claude’s response formatting automatically to enhance readability and reduce token consumption.

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The Output Style Selector is a specialized skill for Claude Code designed to maximize information density and scannability. By analyzing your prompt's intent, it intelligently selects the most effective presentation format—such as structured tables for comparisons, YAML for data, or ultra-concise bullets for quick updates. This automation ensures that complex information is delivered in its most digestible form, reducing the need for follow-up questions while simultaneously saving tokens by avoiding verbose, conversational filler.

Características Principales

Support for multiple output styles including Tables, YAML, HTML, and Bullets
Token-saving 'Ultra-Concise' mode for rapid iterations
Compact style indicators that provide context without cluttering the UI
Manual style overrides using simple bracketed syntax
2 GitHub stars
Automatic intent inference from prompt keywords and task types

Casos de Uso

Generating side-by-side comparisons of technical architectures or libraries
Converting complex logic into structured YAML or JSON for easy parsing
Summarizing long terminal outputs into scannable action items

Acerca de

Características Principales

Support for multiple output styles including Tables, YAML, HTML, and Bullets
Token-saving 'Ultra-Concise' mode for rapid iterations
Compact style indicators that provide context without cluttering the UI
Manual style overrides using simple bracketed syntax
2 GitHub stars
Automatic intent inference from prompt keywords and task types

Casos de Uso

Generating side-by-side comparisons of technical architectures or libraries
Converting complex logic into structured YAML or JSON for easy parsing
Summarizing long terminal outputs into scannable action items