awesome-copilot/plugins/phoenix/skills/phoenix-tracing/references/fundamentals-required-attributes.md

Required and Recommended Attributes

This document covers the required attribute and highly recommended attributes for all OpenInference spans.

Required Attribute

Every span MUST have exactly one required attribute:

{
  "openinference.span.kind": "LLM"
}

Highly Recommended Attributes

While not strictly required, these attributes are highly recommended on all spans as they:

• Enable evaluation and quality assessment
• Help understand information flow through your application
• Make traces more useful for debugging

Input/Output Values

Attribute	Type	Description
input.value	String	Input to the operation (prompt, query, document)
output.value	String	Output from the operation (response, result, answer)

Example:

{
  "openinference.span.kind": "LLM",
  "input.value": "What is the capital of France?",
  "output.value": "The capital of France is Paris."
}

Why these matter:

• Evaluations: Many evaluators (faithfulness, relevance, hallucination detection) require both input and output to assess quality
• Information flow: Seeing inputs/outputs makes it easy to trace how data transforms through your application
• Debugging: When something goes wrong, having the actual input/output makes root cause analysis much faster
• Analytics: Enables pattern analysis across similar inputs or outputs

Phoenix Behavior:

• Input/output displayed prominently in span details
• Evaluators can automatically access these values
• Search/filter traces by input or output content
• Export inputs/outputs for fine-tuning datasets

Valid Span Kinds

There are exactly 9 valid span kinds in OpenInference:

Span Kind	Purpose	Common Use Case
LLM	Language model inference	OpenAI, Anthropic, local LLM calls
EMBEDDING	Vector generation	Text-to-vector conversion
CHAIN	Application flow orchestration	LangChain chains, custom workflows
RETRIEVER	Document/context retrieval	Vector DB queries, semantic search
RERANKER	Result reordering	Rerank retrieved documents
TOOL	External tool invocation	API calls, function execution
AGENT	Autonomous reasoning	ReAct agents, planning loops
GUARDRAIL	Safety/policy checks	Content moderation, PII detection
EVALUATOR	Quality assessment	Answer relevance, faithfulness scoring