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prompt-formatter

Transform vague user requests into COSTAR-based structured prompts for LLMs.

Updated Feb 19, 2026
Search Tags:#llm#prompt-engineering#prompt#structured-prompt#concision#costar
One-click install
npx skills add https://github.com/jonnathan-ls/ai-context-kit --skill prompt-formatter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-formatter
Source: https://github.com/jonnathan-ls/ai-context-kit/tree/main/skills/prompt-formatter
Command: npx skills add https://github.com/jonnathan-ls/ai-context-kit --skill prompt-formatter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams and individuals convert unclear, ambiguous, or under-specified requests into clear, actionable prompts using the COSTAR framework, ensuring consistent prompt quality for LLMs.

Core Features & Use Cases

  • COSTAR-based Prompt Construction: Build a structured prompt with C (Context), O (Objective), S (Style), T (Tone), A (Audience), and R (Response) sections.
  • Dual Output: Generates both a Structured Prompt and a Concise Prompt ready for immediate use.
  • Context-Driven Guidance: Guides the user to define role, context, objectives, audience, and constraints to align AI behavior with goals.

Quick Start

Feed a USER_REQUEST and optional ADDITIONAL_CONTEXT to generate a COSTAR-structured prompt plus a concise prompt for immediate use.

Frequently Asked Questions about prompt-formatter

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

FAQPage Schema
What is the COSTAR framework for prompt engineering?▼

The COSTAR framework structures LLM prompts using Context, Objective, Style, Tone, Audience, and Response sections to align AI behavior with specific goals. It guides users to define explicit role and constraints for consistent prompt quality.

How do I turn a vague request into a structured prompt?▼

To turn a vague request into a structured prompt, feed the raw user request and optional additional context to a prompt formatter. It outputs both a formal COSTAR-based structured prompt and a concise prompt for immediate use.

What is the best way to write context-driven instructions for an LLM?▼

The best way to write context-driven LLM instructions is using a structured prompt framework like COSTAR. This ensures you explicitly define the role, context, objectives, audience, and constraints to produce clear, actionable prompts.

Can I generate a concise prompt alongside a full structured prompt?▼

Yes, prompt formatting tools can generate dual outputs. They produce a formal COSTAR-structured prompt alongside a concise prompt, ensuring you have both detailed context-rich instructions and a shortened version for immediate use.

Why does my LLM output lack consistency across different domains?▼

Your LLM output lacks consistency due to under-specified or ambiguous requests. Converting unclear inputs into precise COSTAR-based prompts with explicit context, style, and tone ensures consistent prompt quality across diverse domains.

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