Phoenix plugins for Claude Code, Cursor and Codex

Everything Claude Code is a Claude Code plugin and toolkit containing configurable agents, skills, slash commands, rules, hooks, contexts, MCP server configurations, scripts, and tests for AI-assisted software development. Its agents delegate tasks such as planning, code review, security review, testing, and build-error resolution. Skills define workflows including test-driven development, security review, continuous learning, and verification; hooks run on Claude Code tool or session events to load and save context, suggest compaction, and evaluate sessions; and rules provide persistent guidance for security, coding style, testing, Git workflow, delegation, and performance. Node.js scripts support Windows, macOS, and Linux and detect a project's preferred package manager from environment settings, project configuration, package.json, lock files, or global configuration. The repository can be installed as a Claude Code plugin or copied into Claude configuration directories manually. It includes a Node.js test suite and is distributed under the MIT license.

Phoenix is an open-source AI observability platform developed by Arize for experimenting with, evaluating, and troubleshooting LLM applications and agents. It traces application runtime with OpenTelemetry-based instrumentation, supports response and retrieval evaluations, and provides versioned datasets, experiment tracking, prompt management, and a playground for comparing models, adjusting parameters, and replaying traced calls. Phoenix also includes PXI, an AI engineering agent for debugging traces and iterating on prompts, plus a remote MCP server for querying traces, datasets, and experiments from MCP clients. It can run locally, in containers, through Kubernetes and Helm, or in the cloud, and is distributed through the `arize-phoenix` Python package, Conda, Docker images, and related TypeScript and Python packages.

Arize Skills is a set of installable skills for AI coding agents, maintained by Arize, that guides agents through adding observability, creating datasets, running experiments and evaluations, and optimizing prompts for LLM applications. The skills use the ax CLI to interact with Arize and include workflows for tracing and debugging applications, OpenInference-based instrumentation, dataset management, experiments, LLM-as-judge evaluators, annotations, prompt optimization, provider credentials, and production monitoring. They can be installed into agents such as Cursor, Claude Code, Codex, GitHub Copilot, and Windsurf through npx, the repository's installers, the ax CLI, or a Claude Code plugin. The repository is licensed under MIT.

Arize Phoenix is an open-source AI observability and evaluation platform developed by Arize AI for tracing, evaluating, and debugging AI agents and LLM applications. It collects traces of LLM requests and the surrounding application execution, displays them in a trace UI, and supports evaluation storage, datasets, experiments, annotations, and result comparisons. Phoenix can use OpenInference telemetry to record execution paths across multiple application steps, helping identify failures in retrieval, tool execution, or model responses; it also supports code evaluations and LLM-as-a-judge evaluations. It can run locally or be self-hosted in another environment.

A public repository of agent skills from Arize AI that connects coding agents to features in the Arize observability interface. The skills let coding agents read production traces and observability data to investigate agent failures and make fixes. The associated workflow uses a five-step regression loop: curate datasets from production traces, score them with evaluators, run baseline experiments, compare changes, and gate merges in continuous integration.