prompt-decorators-usage

Apply standardized prompt decorators to control LLM behavior across modes.

42|10|Updated Feb 28, 2025

Search Tags:#workflow #llm #catalog #prompt #decorators #inline-sigs

Ready to run

npx skills add https://github.com/synaptiai/prompt-decorators --skill prompt-decorators-usage

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-decorators-usage
Source: https://github.com/synaptiai/prompt-decorators/tree/main/claude-code-plugin/skills/prompt-decorators-usage
Command: npx skills add https://github.com/synaptiai/prompt-decorators --skill prompt-decorators-usage

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prompt decorators provide a standardized way to adjust LLM behavior by attaching lightweight signals to prompts, reducing noise and dependency on verbose instructions.

Core Features & Use Cases

Inline sigils, always-on config, and auto mode for flexible prompt customization.
Clear guidance on selecting 1–3 decorators from categorized families (reasoning, structure, tone, verification, meta).
Safe composition with guardrails to avoid conflicting decorators and ensure predictable outputs.

Quick Start

To get started, identify the decoration intent, select 1–3 decorators from the catalogue, decide the delivery method, and present the exact syntax to the user.

Frequently Asked Questions about prompt-decorators-usage

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

FAQPage Schema

What are prompt decorators and how do they control LLM behavior?▼

Prompt decorators are lightweight signals attached to prompts to adjust LLM behavior, reducing noise and dependency on verbose instructions for predictable outputs.

How do I apply prompt decorators to structure and verify LLM outputs?▼

Identify your decoration intent, select 1–3 decorators from categorized families, decide the delivery method, and apply the exact syntax to transform reasoning, structure, tone, or verification.

Can I use inline sigils and always-on config together in LLM workflows?▼

Yes, you can use inline sigils, always-on config, and auto mode together to flexibly customize prompts across varied workflows while maintaining safe composition guardrails.

What is the best way to compose multiple prompt decorators without conflicts?▼

The best way to compose decorators safely is by validating up to three decorators from distinct categories, using built-in guardrails to avoid conflicting decorators and ensure predictable outputs.

How many prompt decorators can I apply in a single LLM request?▼

You can apply a maximum of three prompt decorators in a single request, provided they are selected from distinct categories to prevent composition conflicts.

Why does my prompt decorator transformation fail to verify LLM outputs?▼

Prompt decorator transformations may fail if you select conflicting decorators from the same category, exceeding the validated limit of three decorators from distinct families.