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ai-prompt-manager

Manage AI prompts, features, providers, quotas, and UI components.

Updated Dec 19, 2025
Search Tags:#debugging#prompt engineering#ai#llm#configuration#orchestration
One-click install
npx skills add https://github.com/Spectaculous-Code/raamattu-nyt --skill ai-prompt-manager
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-prompt-manager
Source: https://github.com/Spectaculous-Code/raamattu-nyt/tree/main/.claude/skills/ai-prompt-manager
Command: npx skills add https://github.com/Spectaculous-Code/raamattu-nyt --skill ai-prompt-manager

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the management and configuration of AI prompts, features, and providers within the AI orchestrator system, ensuring efficient and controlled AI interactions.

Core Features & Use Cases

  • Prompt Management: Create, edit, and version AI prompts and templates.
  • Feature Configuration: Register new AI features, define vendor/model bindings, and manage quotas.
  • Debugging & Monitoring: Troubleshoot AI quota errors, monitor usage, and understand costs.
  • UI Integration: Utilize pre-built UI components for AI progress, context preview, and error display.
  • Use Case: A developer needs to add a new AI-powered summarization feature. They use this Skill to register the feature, define the prompt template, select an appropriate AI model (e.g., GPT-4o), configure its parameters, and set up user quotas.

Quick Start

Use the ai-prompt-manager skill to register a new AI feature named 'bible-search-summary' with the 'openrouter' provider and the 'openai/gpt-4o' model.

Frequently Asked Questions about ai-prompt-manager

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

FAQPage Schema
How do I register a new AI feature and bind it to a specific LLM model?▼

Register a new AI feature by defining its name, selecting an LLM provider like openrouter, binding a specific model such as openai/gpt-4o, configuring parameters, and setting user quotas to enable the feature within the orchestrator.

Why am I hitting AI quota errors and how do I monitor LLM usage costs?▼

Troubleshoot AI quota errors and monitor LLM usage costs by accessing the orchestrator's debugging and monitoring tools to track feature consumption, identify quota limits, and understand overall vendor API spending.

Can I integrate AI progress indicators and processing panels into my frontend UI?▼

Integrate AI progress indicators and processing panels into your frontend UI by utilizing the orchestrator's pre-built UI components like AIProgressBar and AIProcessingPanel to display context previews and error states.

What is the best way to version AI prompt templates during prompt engineering?▼

Version AI prompt templates during prompt engineering by using the orchestrator's management interface to edit, save, and track revisions of prompt structures to ensure consistent LLM interactions across application updates.

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