Atlas / Skills / arize-ai / Phoenix Tracing Skill

Phoenix Tracing SkillCAUTION

skills/arize-ai/phoenix-tracing

AI Observability & Evaluation

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
1.0.0
Hosts
3 documented
License
NOASSERTION
Stars
11,942
01

Overview

From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.

OpenInference semantic conventions and instrumentation guides for Phoenix.

Usage

Start with SKILL.md for the index and quick reference.

File Organization

All files in flat references/ directory with semantic prefixes:

  • span-* - Span kinds (LLM, CHAIN, TOOL, etc.)
  • setup-*, instrumentation-* - Getting started guides
  • fundamentals-*, attributes-* - Reference docs
  • annotations-*, export-* - Advanced features

Reference

Read from source at commit 1806650f7d1dOBSERVED · 2026-10-22
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02

Install

Commands as the repository documents them. They are shown, not run.

pip install arize-phoenix-client
pip install arize-phoenix-otel
pip install openinference-instrumentation-openai  # Add others as needed
pip install opentelemetry-instrumentation-anthropic
pip install arize-phoenix-otel
npm install @arizeai/phoenix-otel @arizeai/openinference-core
03

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
codexmentioned
gemini-climentioned
04

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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. (also covers OTel GenAI native instrumentation)
- [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
- [instrumentation-atif-python](references/instrumentation-atif-python.md) - Import ATIF agent trajectories (Claude Code, OpenHands, Codex, etc.)

### 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
- [span-decision](references/span-decision.md) - Decision model calls (routing, classification, scoring) — experimental

### 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

# 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-*
05

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (5)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
.claude/skills
.claude/skills
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
.codex/skills
.codex/skills
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
.cursor/skills/mintlify
.cursor/skills/mintlify
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
.cursor/skills/vercel-react-best-practices
.cursor/skills/vercel-react-best-practices
Why it matters. link not followed
LOWInventory / provenance · inv.symlink · CWE-1104
CLAUDE.md
CLAUDE.md
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-10-22 · audit v0.4.1 · source sha 1806650f7d1dfull audit observations/trust-audit/skill/arize-ai__phoenix-tracing.json · Report an issue / request a re-scan
06

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-221806650f7d1dCAUTIONB89first audit
07

Questions

What does the phoenix-tracing — arize-ai/phoenix skill do?

AI Observability & Evaluation

Is phoenix-tracing — arize-ai/phoenix safe to install?

With care. The audit graded it B (89/100) and found 5 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can phoenix-tracing — arize-ai/phoenix access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does phoenix-tracing — arize-ai/phoenix work with?

Its documentation mentions claude-code, codex and gemini-cli. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (1806650f7d1d), read on 2026-10-22. The repository is watched, and a new audit runs when it changes — this is the first audit.

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