Arize Instrumentation
技能 活跃Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.
To enable users to easily add LLM observability and tracing to their applications using Arize AX by following a guided, agent-assisted workflow.
功能
- Adds Arize AX tracing to LLM applications.
- Two-phase agent-assisted analysis and implementation flow.
- Supports Python, TypeScript/JavaScript, Java, and Go.
- Integrates with LLM providers, frameworks, and OpenTelemetry.
- Provides detailed guidance on manual span creation for tool use.
使用场景
- When a user wants to instrument their application for the first time with Arize AX tracing.
- When a user needs to set up LLM observability from scratch.
- When a user wants to integrate OpenTelemetry or openinference with their LLM application.
- When a user needs to get started with Arize tracing and requires guided setup.
非目标
- Replacing core business logic of the application.
- Generating extensive documentation or summary files beyond the necessary code.
- Embedding literal credential values in generated code.
- Proactively checking `ax` installation or version before it's needed.
工作流
- Phase 0: Environment preflight (confirm scope, identify runtime needs)
- Phase 1: Analysis (scan manifests, check imports, detect existing tracing, identify scope)
- Phase 1 Output: Summarize findings and propose integration
- Phase 2: Implementation (fetch docs, install packages, set credentials, centralize instrumentation, add manual spans if needed)
- Verification (app builds, starts, produces traces; check in Arize or provide blockers)
实践
- Code Analysis
- Observability
- Instrumentation
- Agent-Assisted Development
先决条件
- Access to the codebase
- Python, TypeScript/JavaScript, Java, or Go runtime environment
- Arize API Key and Space ID (to be configured by the user)
Execution
- warning:Pinned dependenciesWhile installation instructions specify packages to install, they do not explicitly mandate pinning versions or provide lockfile generation steps, which could lead to unexpected behavior with dependency updates.
安装
npx skills add github/awesome-copilot通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
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