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phoenix-tracing — GitHub Copilot skill for Phoenix tracing

This skill guides OpenInference tracing for LLM apps with Phoenix. Use it to set up instrumentation, define custom spans, or prepare tracing for production.

Install into GitHub Copilot · Skills CLI (Vercel) All methods and platforms ↓
npx skills add github/awesome-copilot --skill phoenix-tracing
Open on GitHub

What phoenix-tracing does

The reference material covers setup for Python and TypeScript, automatic and manual instrumentation, span kinds, and their attributes. It also includes guidance on grouping traces into projects and sessions, adding metadata, batching data, masking PII, and annotating spans with feedback.

Start with setup-python or setup-typescript, then choose automatic or manual instrumentation. A Phoenix server is required. Python projects need arize-phoenix-otel; TypeScript projects need @arizeai/phoenix-otel.

Install it when you are adding tracing or need to follow OpenInference conventions. Skip it if your project does not use Phoenix.

What it helps with

  • configure a Phoenix endpoint for a Python or TypeScript app
  • add automatic tracing for a supported framework
  • create custom spans for LLM operations
  • group traces by project or conversation session
  • prepare batching and PII masking for production

Example prompts for the agent

  • Set up Phoenix tracing in my Python app and add automatic OpenAI instrumentation.
  • Create custom spans for each step in this LLM pipeline using OpenInference conventions.
  • How should I group conversation traces into sessions and attach feedback to spans?

How to install phoenix-tracing

1Skills CLI (Vercel)

npx skills add github/awesome-copilot --skill phoenix-tracing

2GitHub CLI

gh skill install github/awesome-copilot phoenix-tracing

3Manually: put the files in place

.github/skills/phoenix-tracing/SKILL.md

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Questions about phoenix-tracing

How do I install phoenix-tracing in GitHub Copilot?

Run npx skills add github/awesome-copilot --skill phoenix-tracing or gh skill install github/awesome-copilot phoenix-tracing.

What does phoenix-tracing do?

It provides references for instrumenting LLM applications with OpenInference tracing in Phoenix, covering setup, instrumentation, span types, and production workflows.

What does phoenix-tracing require?

It requires a Phoenix server. Python projects also need arize-phoenix-otel; TypeScript projects need @arizeai/phoenix-otel.

Source text

SKILL.md · Apache-2.0
---
name: phoenix-tracing
description: OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
license: Apache-2.0
compatibility: Requires Phoenix server. Python skills need arize-phoenix-otel; TypeScript skills need @arizeai/phoenix-otel.
metadata:
  author: [email protected]
  version: "1.0.0"
  languages: "Python, TypeScript"
---

# 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](references/setup-python.md) - Install arize-phoenix-otel, configure endpoint
- [setup-typescript](references/setup-typescript.md) - Install @arizeai/phoenix-otel, configure endpoint

### 2. Instrumentation

- [instrumentation-auto-python](references/instrumentation-auto-python.md) - Auto-instrument OpenAI, LangChain, etc.
- [instrumentation-auto-typescript](references/instrumentation-auto-typescript.md) - Auto-instrument supported frameworks
- [instrumentation-manual-python](references/instrumentation-manual-python.md) - Custom spans with decorators
- [instrumentation-manual-typescript](references/instrumentation-manual-typescript.md) - Custom spans with wrappers

### 3. Span Types (with full attribute schemas)

- [span-llm](references/span-llm.md) - LLM API calls (model, tokens, messages, cost)
- [span-chain](references/span-chain.md) - Multi-step workflows and pipelines
- [span-retriever](references/span-retriever.md) - Document retrieval (documents, scores)
- [span-tool](references/span-tool.md) - Function/API calls (name, parameters)
- [span-agent](references/span-agent.md) - Multi-step reasoning agents
- [span-embedding](references/span-embedding.md) - Vector generation
- [span-reranker](references/span-reranker.md) - Document re-ranking
- [span-guardrail](references/span-guardrail.md) - Safety checks
- [span-evaluator](references/span-evaluator.md) - LLM evaluation

### 4. Organization

- [projects-python](references/projects-python.md) / [projects-typescript](references/projects-typescript.md) - Group traces by application
- [sessions-python](references/sessions-python.md) / [sessions-typescript](references/sessions-typescript.md) - Track conversations

### 5. Enrichment

- [metadata-python](references/metadata-python.md) / [metadata-typescript](references/metadata-typescript.md) - Custom attributes

### 6. Production (CRITICAL)

- [production-python](references/production-python.md) / [production-typescript](references/production-typescript.md) - Batch processing, PII masking

### 7. Feedback

- [annotations-overview](references/annotations-overview.md) - Feedback concepts
- [annotations-python](references/annotations-python.md) / [annotations-typescript](references/annotations-typescript.md) - Add feedback to spans

### Reference Files

- [fundamentals-overview](references/fundamentals-overview.md) - Traces, spans, attributes basics
- [fundamentals-required-attributes](references/fundamentals-required-attributes.md) - Required fields per span type
- [fundamentals-universal-attributes](references/fundamentals-universal-attributes.md) - Common attributes (user.id, session.id)
- [fundamentals-flattening](references/fundamentals-flattening.md) - JSON flattening rules

## 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:**

```bash
# 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:**
1. Start with setup-{lang} for your language
2. Choose instrumentation-auto-{lang} OR instrumentation-manual-{lang}
3. Reference span-{type} files as needed for specific operations
4. See fundamentals-* files for attribute specifications

## References

**Phoenix Documentation:**

- [Phoenix Documentation](https://docs.arize.com/phoenix)
- [OpenInference Spec](https://github.com/Arize-ai/openinference/tree/main/spec)

**Python API Documentation:**

- [Python OTEL Package](https://arize-phoenix.readthedocs.io/projects/otel/en/latest/) - `arize-phoenix-otel` API reference
- [Python Client Package](https://arize-phoenix.readthedocs.io/projects/client/en/latest/) - `arize-phoenix-client` API reference

**TypeScript API Documentation:**

- [TypeScript Packages](https://arize-ai.github.io/phoenix/) - `@arizeai/phoenix-otel`, `@arizeai/phoenix-client`, and other TypeScript packages

© [email protected] · Apache-2.0 · github/awesome-copilot

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