II.
LibraryProcess overview
Reference · livelib-process:ai-agents-conversational--conversation-quality-testing
conversation-quality-testing overview
Conversation Quality Testing and Metrics - Process for measuring conversational AI quality including intent accuracy, dialogue success rate, user satisfaction (CSAT), response appropriateness, and conversation coherence.
Attributes
displayName
conversation-quality-testing
description
Conversation Quality Testing and Metrics - Process for measuring conversational AI quality including
intent accuracy, dialogue success rate, user satisfaction (CSAT), response appropriateness, and conversation coherence.
libraryPath
library/specializations/ai-agents-conversational/conversation-quality-testing.js
specialization
ai-agents-conversational
references
- - DSTC: https://dstc.community/ - Conversation Quality Metrics: https://aclanthology.org/2020.nlp4convai-1.8/
example
const result = await orchestrate('specializations/ai-agents-conversational/conversation-quality-testing', {
systemName: 'customer-chatbot',
qualityMetrics: ['intent-accuracy', 'dialogue-success', 'csat', 'coherence'],
testDataset: { conversations: 100 }
});
usesAgents
- data-preparer
- llm-judge
- dialogue-tester
- coherence-evaluator
- feedback-analyst
- report-generator
Outgoing edges
lib_applies_to_domain1
- domain:software-engineering·DomainSoftware Engineering
lib_belongs_to_specialization1
- specialization:ai-agents-conversational·Specialization
lib_implements_workflow3
- workflow:code-review·Workflow
- workflow:code-review·Workflow
- workflow:prompt-engineering-iteration·WorkflowPrompt Engineering Iteration
uses_agent1
- lib-agent:ai-agents-conversational--llm-judge·LibraryAgentllm-judge
Incoming edges
None.