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/phoenix-tracing

@4214189 official
by githubgithub/awesome-copilot40k stars
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OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.

Use this Skill: https://skilld.dev/gh/github/awesome-copilot/phoenix-tracing

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referencesspan-tool.md

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TOOL Spans

Purpose

TOOL spans represent external tool or function invocations (API calls, database queries, calculators, custom functions).

Required Attributes

Attribute Type Description Required
openinference.span.kind String Must be "TOOL" Yes
tool.name String Tool/function name Recommended

Attribute Reference

Tool Execution Attributes

Attribute Type Description
tool.name String Tool/function name
tool.description String Tool purpose/description
tool.parameters String (JSON) JSON schema defining the tool's parameters
input.value String (JSON) Actual input values passed to the tool
output.value String Tool output/result
output.mime_type String Result content type (e.g., "application/json")

Examples

API Call Tool

{
  "openinference.span.kind": "TOOL",
  "tool.name": "get_weather",
  "tool.description": "Fetches current weather for a location",
  "tool.parameters": "{\"type\": \"object\", \"properties\": {\"location\": {\"type\": \"string\"}, \"units\": {\"type\": \"string\", \"enum\": [\"celsius\", \"fahrenheit\"]}}, \"required\": [\"location\"]}",
  "input.value": "{\"location\": \"San Francisco\", \"units\": \"celsius\"}",
  "output.value": "{\"temperature\": 18, \"conditions\": \"partly cloudy\"}"
}

Calculator Tool

{
  "openinference.span.kind": "TOOL",
  "tool.name": "calculator",
  "tool.description": "Performs mathematical calculations",
  "tool.parameters": "{\"type\": \"object\", \"properties\": {\"expression\": {\"type\": \"string\", \"description\": \"Math expression to evaluate\"}}, \"required\": [\"expression\"]}",
  "input.value": "{\"expression\": \"2 + 2\"}",
  "output.value": "4"
}

Database Query Tool

{
  "openinference.span.kind": "TOOL",
  "tool.name": "sql_query",
  "tool.description": "Executes SQL query on user database",
  "tool.parameters": "{\"type\": \"object\", \"properties\": {\"query\": {\"type\": \"string\", \"description\": \"SQL query to execute\"}}, \"required\": [\"query\"]}",
  "input.value": "{\"query\": \"SELECT * FROM users WHERE id = 123\"}",
  "output.value": "[{\"id\": 123, \"name\": \"Alice\", \"email\": \"alice@example.com\"}]",
  "output.mime_type": "application/json"
}

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub9d

    The phoenix-tracing skill provides comprehensive documentation and implementation guides for instrumenting LLM applications with Phoenix and OpenInference semantic conventions. It covers setup, manual and auto-instrumentation, and production best practices for both Python and TypeScript, with a strong focus on secure data handling and PII masking.

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    Risk: LOW · No issues

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    Score: 93/100 · 2 sections analyzed

Signed by skilld at 4214189. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 2 months ago
Other metadata
compatibility
Requires Phoenix server. Python skills need arize-phoenix-otel; TypeScript skills need @arizeai/phoenix-otel.
metadata
{
  "author": "oss@arize.com",
  "version": "1.0.0",
  "languages": "Python, TypeScript"
}
  • Python
  • TypeScript
  • phoenix
  • tracing
  • openinference
  • llm-observability
  • instrumentation
  • otel
  • arize

README badge

README badge for github/awesome-copilot/phoenix-tracing

Instruments LLM applications with OpenInference tracing in Phoenix, supporting auto-instrumentation of frameworks like OpenAI and LangChain or custom manual spans. Covers setup, span types (LLM calls, retrievers, agents, evaluators), production deployment with PII masking, and feedback annotation in Python and TypeScript.

Generated from the current SKILL.md.

Does this skill work with both Python and TypeScript?
Yes. The skill provides separate setup, instrumentation, and production guides for both Python (arize-phoenix-otel) and TypeScript (@arizeai/phoenix-otel).
What do I need to install to use this skill?
For Python: arize-phoenix-otel package. For TypeScript: @arizeai/phoenix-otel package. Both require a running Phoenix server endpoint.
Can I auto-instrument frameworks like OpenAI or LangChain?
Yes. The skill includes instrumentation-auto-{lang} references that cover auto-instrumentation for supported frameworks in both languages.
How do I track custom spans for my own operations?
Use the instrumentation-manual-{lang} references to create custom spans with decorators (Python) or wrappers (TypeScript), then refer to span-{type} files for the appropriate attribute schema.
Does this skill cover production deployment concerns?
Yes. The production-{lang} references address batch processing, PII masking, and deployment patterns for production environments.

Generated from the current SKILL.md. These answers refresh after source changes.