skills.rest
Ankh-Studio
Ankh-StudioOFFICIAL
Explore all skills by this author →
GitHub

prompt

Evaluate natural language prompts against a structured rubric with weighted scores.

Updated Mar 10, 2026
Search Tags:#feedback#prompt engineering#ai#llm#evaluation#rubric
One-click install
npx skills add https://github.com/Ankh-Studio/copilot-enterprise-eval-plugin --skill prompt-ankh-studio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt
Source: https://github.com/Ankh-Studio/copilot-enterprise-eval-plugin/tree/main/skills/prompt
Command: npx skills add https://github.com/Ankh-Studio/copilot-enterprise-eval-plugin --skill prompt-ankh-studio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the evaluation of prompts against a defined rubric, providing objective scoring and actionable feedback for prompt improvement.

Core Features & Use Cases

  • Prompt Evaluation: Assesses prompts based on clarity, specificity, context, constraints, and examples.
  • Scoring System: Assigns scores from 0-4 for each criterion and calculates a weighted total.
  • Use Case: Improve the quality of prompts used for AI model interactions by systematically identifying weaknesses and suggesting enhancements.

Quick Start

Use the prompt skill to evaluate the prompt in the file .github/prompts/example.prompt.md.

Frequently Asked Questions about prompt

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

FAQPage Schema
How do I evaluate prompt quality against a rubric for AI models?▼

To evaluate prompt quality, assess natural language prompts against a structured rubric measuring clarity, specificity, context, constraints, and examples, assigning weighted scores from 0-4 to quantify overall effectiveness.

What criteria should prompt evaluation include to improve LLM interactions?▼

Prompt evaluation criteria for LLM interactions should include clarity, specificity, context, constraints, and examples, providing objective scoring and actionable feedback for iterative prompt refinement.

How do I score and refine natural language prompts systematically?▼

You can score and refine natural language prompts by applying a predefined evaluation rubric that assigns 0-4 points per criterion, calculates a weighted total, and identifies weaknesses to facilitate iterative prompt enhancement.

Do I need a predefined rubric to evaluate prompt engineering quality?▼

Yes, evaluating prompt engineering quality requires a predefined prompt evaluation rubric and a scoring mechanism to objectively quantify prompt performance and generate detailed feedback for AI applications.

What is the best way to automate prompt evaluation for AI applications?▼

The best way to automate prompt evaluation for AI applications is using a tool that systematically assesses prompts against a defined rubric, generating objective weighted scores and actionable feedback for prompt improvement.

Related Skills

Explore More Software Engineering Skills→
Ankh-StudioAnkh-Studio

prompt-evaluation

Evaluate prompt quality against clarity, specificity, context, constraints, and examples.

Official
Intermediate
coval-aicoval-ai
2

review-llm-annotations-and-improve-prompt

Analyze human versus LLM judge annotation discrepancies to refine evaluation prompts.

Official
Advanced
EngineerWithAIEngineerWithAI
4

llm-evaluation

Evaluate LLM applications with automated metrics, human feedback, and benchmarking.

Official
Advanced
rohunvorarohunvora
5

advanced-evaluation

Automate LLM-as-a-judge scoring, pairwise comparison, and rubric generation with bias mitigation.

Community
Advanced