prompt_refiner

Name: prompt_refiner
Availability: InStock
Author: enduser123

Refine prompts with constitutional compliance checks and cognitive technique annotations.

Updated Apr 26, 2026

Search Tags:#refinement #llm #compliance #triage #prompt #constitutional

Ready to run

npx skills add https://github.com/EndUser123/cc-marketplace --skill prompt-refiner-enduser123

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt_refiner
Source: https://github.com/EndUser123/cc-marketplace/tree/main/plugins/cc-skills-meta/skills/prompt_refiner
Command: npx skills add https://github.com/EndUser123/cc-marketplace --skill prompt-refiner-enduser123

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prompt refinement to enforce constitutional compliance and integrate cognitive techniques into high-stakes LLM interactions, reducing risk and increasing reliability.

Core Features & Use Cases

Meta-prompt orchestration: provides structured prompt templates and triage paths for prompt design.
Constitutional compliance: enforces constraints and checks before prompt deployment.
Use Case: When building enterprise LLM workflows, use this to guide prompts through analysis, triage, and output validation.

Quick Start

Provide a refined prompt by analyzing the input, routing it through the correct cognitive approach, and applying constitutional checks.

Frequently Asked Questions about prompt_refiner

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

FAQPage Schema

How do I enforce constitutional compliance in LLM prompts for high-reliability workflows?▼

Prompt refinement for constitutional compliance applies cognitive techniques like Chain of Thought and Tree of Thought to structure interactions. It analyzes the input prompt, routes it through the correct cognitive approach, and applies checks to increase reliability in high-stakes LLM tasks.

What's the best way to integrate cognitive techniques into LLM prompt engineering?▼

Prompt refinement validates LLM outputs by applying tiered decision logic and constitutional checks after routing the prompt through the correct cognitive approach. This process generates quality scores and cognitive technique annotations to ensure the interaction meets high-reliability constraints.

How do I add triage routing and validation to my LLM prompt design?▼

You add triage routing to LLM prompt design by using meta-prompt orchestration templates. These templates analyze the input prompt, route it through tiered decision logic to the appropriate cognitive strategy, and validate the final output against constitutional constraints.

Can I use prompt refinement for multi-agent and analysis tasks in enterprise AI?▼

Yes, you can use prompt refinement for multi-agent and analysis tasks in enterprise AI. The process applies structured meta-prompt orchestration and constitutional compliance checks to guide high-reliability workflows, including complex analysis and triage routing scenarios.