arize-instrumentation

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.

by github 38k GitHub stars MIT Updated Aug 18, 2026
arize-instrumentation skill by github
arize-instrumentation — Integrations skill by github

Overview

arize-instrumentation is an open-source integrations skill for Claude Code and compatible agents, published by github. Its author describes it as: “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 instru…”. The project has 38k stars on GitHub and is available under the MIT license. Add it to your setup with `git clone https://github.com/github/awesome-copilot ~/.claude/skills/arize-instrumentation`.

What arize-instrumentation does

Use this skill when the user wants to **add Arize AX tracing** to their application. Follow the **two-phase, agent-assisted flow** from the Agent-Assisted Tracing Setup and the Arize AX Tracing — Agent Setup Prompt.

What’s inside

The SKILL.md for arize-instrumentation is organised into these sections:

  • Quick start (for the user)
  • Core principles
  • Phase 0: Environment preflight
  • Phase 1: Analysis (read-only)
  • Steps
  • What to identify
  • Phase 1 output
  • Integration routing and docs
  • Phase 2: Implementation
  • Implementation rules
  • Enriching traces: manual spans for tool use and agent loops
  • Why doesn't the auto-instrumentor do this?

Installation

Add arize-instrumentation to your agent with:

git clone https://github.com/github/awesome-copilot ~/.claude/skills/arize-instrumentation

Review a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.

Supported agents

License

arize-instrumentation is published under the MIT license.

Strengths

  • Clear MIT license — safe to read and adapt within its terms
  • Ships in github/awesome-copilot, an established project with 37,982 GitHub stars
  • Works with GitHub Copilot
  • Actively maintained — repository updated in the last 90 days

Author

github 41 skills in the catalog · GitHub profile ↗
View skills

Topics

Alternatives to arize-instrumentation

Similar skills from other repositories:

Need a skill like this, tailored to your team?Build a custom skill →

Frequently asked questions

What does arize-instrumentation do?
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.
How do I install arize-instrumentation?
Run git clone https://github.com/github/awesome-copilot ~/.claude/skills/arize-instrumentation in your agent, then reload your skills. Review the source at https://github.com/github/awesome-copilot before installing.
Is arize-instrumentation free to use?
Yes. arize-instrumentation is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
Which agents does arize-instrumentation work with?
arize-instrumentation lists GitHub Copilot — named in its SKILL.md, its plugin marketplace or its repository topics. Skills use the portable SKILL.md format, so other agents that read that format may load it too.
Where does arize-instrumentation come from?
arize-instrumentation ships inside github/awesome-copilot, a repository that contains 41 catalogued skills in total. The repository's 37,982 GitHub stars apply to that whole collection, not to this skill on its own.

Create or register a canvas extension in the awesome-copilot repository. Use when asked to scaffold a new canvas extension, create its plugin.json, add a reusable extension to one or more plugins, or migrate extension metadata. Extensions are reusable source under extensions/; shippable plugin manifests belong under plugins/.

Official GitHub Copilot
38k GitHub stars MIT Updated Aug 18, 2026 Free

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

Official GitHub Copilot
38k GitHub stars MIT Updated Aug 18, 2026 Free

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

Official GitHub Copilot
38k GitHub stars MIT Updated Aug 18, 2026 Free

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

Official GitHub Copilot
38k GitHub stars MIT Updated Aug 18, 2026 Free

Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.

Official GitHub Copilot
38k GitHub stars MIT Updated Aug 18, 2026 Free