phoenix-tracing▌
arize-ai/phoenix · updated Apr 23, 2026
Comprehensive guide for instrumenting LLM applications with OpenInference tracing in Phoenix. Contains reference files covering setup, instrumentation, span types, and production deployment.
Phoenix Tracing
Comprehensive guide for instrumenting LLM applications with OpenInference tracing in Phoenix. Contains reference files covering setup, instrumentation, span types, and production deployment.
When to Apply
Reference these guidelines when:
- Setting up Phoenix tracing (Python or TypeScript)
- Creating custom spans for LLM operations
- Adding attributes following OpenInference conventions
- Deploying tracing to production
- Querying and analyzing trace data
Reference Categories
| Priority | Category | Description | Prefix |
|---|---|---|---|
| 1 | Setup | Installation and configuration | setup-* |
| 2 | Instrumentation | Auto and manual tracing | instrumentation-* |
| 3 | Span Types | 9 span kinds with attributes | span-* |
| 4 | Organization | Projects and sessions | projects-*, sessions-* |
| 5 | Enrichment | Custom metadata | metadata-* |
| 6 | Production | Batch processing, masking | production-* |
| 7 | Feedback | Annotations and evaluation | annotations-* |
Quick Reference
1. Setup (START HERE)
- setup-python - Install arize-phoenix-otel, configure endpoint
- setup-typescript - Install @arizeai/phoenix-otel, configure endpoint
2. Instrumentation
- instrumentation-auto-python - Auto-instrument OpenAI, LangChain, etc.
- instrumentation-auto-typescript - Auto-instrument supported frameworks
- instrumentation-manual-python - Custom spans with decorators
- instrumentation-manual-typescript - Custom spans with wrappers
3. Span Types (with full attribute schemas)
- span-llm - LLM API calls (model, tokens, messages, cost)
- span-chain - Multi-step workflows and pipelines
- span-retriever - Document retrieval (documents, scores)
- span-tool - Function/API calls (name, parameters)
- span-agent - Multi-step reasoning agents
- span-embedding - Vector generation
- span-reranker - Document re-ranking
- span-guardrail - Safety checks
- span-evaluator - LLM evaluation
4. Organization
- projects-python / projects-typescript - Group traces by application
- sessions-python / sessions-typescript - Track conversations
5. Enrichment
- metadata-python / metadata-typescript - Custom attributes
6. Production (CRITICAL)
- production-python / production-typescript - Batch processing, PII masking
7. Feedback
- annotations-overview - Feedback concepts
- annotations-python / annotations-typescript - Add feedback to spans
Reference Files
- fundamentals-overview - Traces, spans, attributes basics
- fundamentals-required-attributes - Required fields per span type
- fundamentals-universal-attributes - Common attributes (user.id, session.id)
- fundamentals-flattening - JSON flattening rules
- attributes-messages - Chat message format
- attributes-metadata - Custom metadata schema
- attributes-graph - Agent workflow attributes
- attributes-exceptions - Error tracking
Common Workflows
- Quick Start: setup-{lang} → instrumentation-auto-{lang} → Check Phoenix
- Custom Spans: setup-{lang} → instrumentation-manual-{lang} → span-{type}
- Session Tracking: sessions-{lang} for conversation grouping patterns
- Production: production-{lang} for batching, masking, and deployment
How to Use This Skill
Navigation Patterns:
# By category prefix
references/setup-* # Installation and configuration
references/instrumentation-* # Auto and manual tracing
references/span-* # Span type specifications
references/sessions-* # Session tracking
references/production-* # Production deployment
references/fundamentals-* # Core concepts
references/attributes-* # Attribute specifications
# By language
references/*-python.md # Python implementations
references/*-typescript.md # TypeScript implementations
Reading Order:
- Start with setup-{lang} for your language
- Choose instrumentation-auto-{lang} OR instrumentation-manual-{lang}
- Reference span-{type} files as needed for specific operations
- See fundamentals-* files for attribute specifications
References
Phoenix Documentation:
Python API Documentation:
- Python OTEL Package -
arize-phoenix-otelAPI reference - Python Client Package -
arize-phoenix-clientAPI reference
TypeScript API Documentation:
- TypeScript Packages -
@arizeai/phoenix-otel,@arizeai/phoenix-client, and other TypeScript packages
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★62 reviews- ★★★★★Pratham Ware· Dec 28, 2024
Useful defaults in phoenix-tracing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Chinedu Verma· Dec 28, 2024
Solid pick for teams standardizing on skills: phoenix-tracing is focused, and the summary matches what you get after install.
- ★★★★★Emma Haddad· Dec 20, 2024
I recommend phoenix-tracing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Advait Mensah· Dec 16, 2024
phoenix-tracing has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Luis Okafor· Dec 12, 2024
phoenix-tracing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Camila Yang· Nov 19, 2024
We added phoenix-tracing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Advait Abbas· Nov 7, 2024
phoenix-tracing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Min Gupta· Nov 3, 2024
phoenix-tracing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Luis Abbas· Oct 26, 2024
We added phoenix-tracing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Emma Garcia· Oct 22, 2024
Registry listing for phoenix-tracing matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 62