prompt-optimizer

Rewrite rough prompt drafts into polished, ready-to-send instructions.

Updated Mar 11, 2026

Search Tags:#prompt engineering #prompt optimization #chatgpt #rewrite #llm prompting #structured instructions #copy-paste prompt

Ready to run

npx skills add https://github.com/selfagency/agentsy --skill prompt-optimizer-selfagency

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-optimizer
Source: https://github.com/selfagency/agentsy/tree/main/.agents/skills/prompt-optimizer
Command: npx skills add https://github.com/selfagency/agentsy --skill prompt-optimizer-selfagency

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you transform an unfinished or poorly formed request into a polished, copy-pasteable prompt that reliably works in chat with any LLM—without placeholders or template variables.

Core Features & Use Cases

Chat-ready prompt rewriting: Converts rough prompts, drafts, and task descriptions into a single final instruction for an LLM inside a chat interface.
No-placeholder guarantee: Ensures the output never includes fill-in variables, bracketed placeholders, or template syntax—so it can be sent as-is.
Self-contained or input-asking behavior: If you provide content, it bakes it into the prompt; if you only describe a task type, it tells the model to request the specific missing inputs from you before drafting.

Quick Start

Ask the AI to optimize your prompt for a specific model and paste your rough draft or describe the task you want the LLM to complete.

Frequently Asked Questions about prompt-optimizer

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

FAQPage Schema

How do I optimize a rough prompt for ChatGPT and other LLMs?▼

Prompt optimization rewrites your rough drafts into polished, copy-pasteable instructions for chat. The Skill outputs a single fenced code-block containing no placeholders, instructing the model to request missing inputs if needed.

How do I rewrite a prompt so it has no placeholders or template variables?▼

The Skill rewrites prompts to guarantee no placeholders or template variables appear. It embeds your provided content directly into the instruction or tells the model to request missing inputs before drafting.

What is the best way to prepare reusable chat prompts for described task classes?▼

Preparing reusable chat prompts involves describing a task type to generate a self-contained instruction. The Skill creates a prompt that tells the model to request specific missing inputs from you before drafting.

Can I use this prompt optimizer if I only have a rough idea and no drafted content?▼

Yes, if you only describe a task class without content, the Skill produces a prompt that instructs the model to request specific missing inputs from you before drafting.

Why does my LLM output vary when I use rough prompts in chat?▼

Rough prompts lack structure and depth cues, causing output variance. This Skill upgrades drafts into structured instructions ending with a deliberate depth-of-reasoning cue to improve reliability.