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llm-integrator

Integrate Claude or GPT APIs with sentiment-driven emotion mapping for mascot chat experiences.

18|1|Updated Sep 3, 2025
Search Tags:#API integration#Claude#LLM#AI#conversational AI#sentiment analysis#GPT#chatbot
One-click install
npx skills add https://github.com/joshtol/emotive-engine --skill llm-integrator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-integrator
Source: https://github.com/joshtol/emotive-engine/tree/main/skills/llm-integrator
Command: npx skills add https://github.com/joshtol/emotive-engine --skill llm-integrator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @anthropic-ai/sdk, lodash.

What problem does it solve?

This Skill bridges the gap between Large Language Models (LLMs) and visual interfaces, automating sentiment analysis and emotion mapping to create emotionally intelligent, conversational AI experiences.

Core Features & Use Cases

  • Claude/GPT Integration: Seamlessly connect to Anthropic Claude or OpenAI GPT APIs for robust conversational AI capabilities.
  • Sentiment-Driven Emotions: Automatically detect sentiment from LLM responses and map it to appropriate mascot emotions, making AI interactions more human-like.
  • Context-Aware Responses: Tailor LLM prompts and emotion mappings based on specific use cases (e.g., retail, healthcare) for highly relevant interactions.
  • Use Case: You're building a customer support chatbot. Use this skill to integrate Claude, enabling the emotive-mascot to display 'concern' when a user reports an issue and 'joy' when a solution is found, making the interaction more human-like.

Quick Start

Use the llm-integrator skill to set up a basic Claude API connection and detect sentiment from a user message, mapping it to a mascot emotion.

Frequently Asked Questions about llm-integrator

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

FAQPage Schema
How do I integrate Claude or GPT APIs to create emotion-aware chatbots?▼

Integrating Claude or GPT APIs enables emotion-aware chatbots by routing user messages to LLM providers, analyzing sentiment from responses, and mapping emotions to visual mascot states. The llm-integrator skill automates this workflow with built-in sentiment detection and emotion mapping for conversational interfaces.

What's the best way to add sentiment analysis to LLM responses?▼

Sentiment analysis on LLM responses detects emotional tone and maps it to mascot emotions, creating human-like interactions. This skill implements automatic sentiment-driven emotion mapping so responses trigger appropriate visual or behavioral reactions without manual classification.

Can I use Claude API with sentiment-driven emotion responses in customer support?▼

Yes. You can connect Claude API through this skill to build customer support chatbots that display concern during issue reporting and joy when solutions resolve problems, making interactions feel more human and emotionally responsive.

Do I need system prompts and error handling for LLM-based conversational interfaces?▼

System-context prompts and error handling are essential for reliable LLM integrations. This skill includes both, plus usage reporting, to ensure robust message routing, consistent emotion mapping, and graceful failure across retail, healthcare, and education domains.

How does sentiment analysis map to mascot emotions in real-time?▼

Sentiment analysis extracts emotional tone from LLM outputs and maps it to predefined mascot emotion states in real-time. The skill automates this detection and mapping process, eliminating manual emotion assignment while maintaining context-aware responses for specific use cases.

What's required before connecting LLM APIs for emotion-aware interactions?▼

You need API credentials for Claude or GPT, context-specific prompts tailored to your domain, and emotion mapping definitions. The skill requires @anthropic-ai/sdk and lodash as dependencies to handle API integration, sentiment detection, and emotion routing.

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